done
This commit is contained in:
gg12 darfren
parent
0e9d03446d
commit
f49b209552
486
lec4.ipynb
486
lec4.ipynb
@ -9,7 +9,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 12,
|
"execution_count": 2,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -37,7 +37,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 13,
|
"execution_count": 3,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -643,7 +643,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 23,
|
"execution_count": 4,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -717,7 +717,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 24,
|
"execution_count": 5,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -908,7 +908,7 @@
|
|||||||
"[2217 rows x 8 columns]"
|
"[2217 rows x 8 columns]"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 24,
|
"execution_count": 5,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -950,7 +950,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 25,
|
"execution_count": 6,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -993,7 +993,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 26,
|
"execution_count": 7,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1082,7 +1082,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 29,
|
"execution_count": 8,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1121,297 +1121,297 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 30,
|
"execution_count": 9,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/html": [
|
"text/html": [
|
||||||
"<style type=\"text/css\">\n",
|
"<style type=\"text/css\">\n",
|
||||||
"#T_98a81_row0_col0, #T_98a81_row0_col1, #T_98a81_row0_col2, #T_98a81_row0_col3, #T_98a81_row2_col2, #T_98a81_row3_col2, #T_98a81_row3_col3 {\n",
|
"#T_17992_row0_col0, #T_17992_row0_col1, #T_17992_row0_col2, #T_17992_row0_col3, #T_17992_row2_col2, #T_17992_row3_col2, #T_17992_row3_col3 {\n",
|
||||||
" background-color: #a8db34;\n",
|
" background-color: #a8db34;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row0_col4, #T_98a81_row0_col5, #T_98a81_row0_col6, #T_98a81_row0_col7 {\n",
|
"#T_17992_row0_col4, #T_17992_row0_col5, #T_17992_row0_col6, #T_17992_row0_col7 {\n",
|
||||||
" background-color: #da5a6a;\n",
|
" background-color: #da5a6a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col0 {\n",
|
"#T_17992_row1_col0 {\n",
|
||||||
" background-color: #86d549;\n",
|
" background-color: #86d549;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col1 {\n",
|
"#T_17992_row1_col1 {\n",
|
||||||
" background-color: #7ad151;\n",
|
" background-color: #7ad151;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col2 {\n",
|
"#T_17992_row1_col2 {\n",
|
||||||
" background-color: #a5db36;\n",
|
" background-color: #a5db36;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col3 {\n",
|
"#T_17992_row1_col3 {\n",
|
||||||
" background-color: #98d83e;\n",
|
" background-color: #98d83e;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col4 {\n",
|
"#T_17992_row1_col4 {\n",
|
||||||
" background-color: #d45270;\n",
|
" background-color: #d45270;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col5, #T_98a81_row2_col5 {\n",
|
"#T_17992_row1_col5, #T_17992_row2_col5 {\n",
|
||||||
" background-color: #d04d73;\n",
|
" background-color: #d04d73;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col6 {\n",
|
"#T_17992_row1_col6 {\n",
|
||||||
" background-color: #d5546e;\n",
|
" background-color: #d5546e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row1_col7, #T_98a81_row2_col7 {\n",
|
"#T_17992_row1_col7, #T_17992_row2_col7 {\n",
|
||||||
" background-color: #d24f71;\n",
|
" background-color: #d24f71;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row2_col0 {\n",
|
"#T_17992_row2_col0 {\n",
|
||||||
" background-color: #a2da37;\n",
|
" background-color: #a2da37;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row2_col1 {\n",
|
"#T_17992_row2_col1 {\n",
|
||||||
" background-color: #6ccd5a;\n",
|
" background-color: #6ccd5a;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row2_col3 {\n",
|
"#T_17992_row2_col3 {\n",
|
||||||
" background-color: #9dd93b;\n",
|
" background-color: #9dd93b;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row2_col4, #T_98a81_row2_col6 {\n",
|
"#T_17992_row2_col4, #T_17992_row2_col6 {\n",
|
||||||
" background-color: #d9586a;\n",
|
" background-color: #d9586a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col0 {\n",
|
"#T_17992_row3_col0 {\n",
|
||||||
" background-color: #1e9b8a;\n",
|
" background-color: #1e9b8a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col1 {\n",
|
"#T_17992_row3_col1 {\n",
|
||||||
" background-color: #23888e;\n",
|
" background-color: #23888e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col4 {\n",
|
"#T_17992_row3_col4 {\n",
|
||||||
" background-color: #b42e8d;\n",
|
" background-color: #b42e8d;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col5, #T_98a81_row5_col6 {\n",
|
"#T_17992_row3_col5, #T_17992_row5_col6 {\n",
|
||||||
" background-color: #b52f8c;\n",
|
" background-color: #b52f8c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col6 {\n",
|
"#T_17992_row3_col6 {\n",
|
||||||
" background-color: #bf3984;\n",
|
" background-color: #bf3984;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row3_col7, #T_98a81_row4_col6 {\n",
|
"#T_17992_row3_col7, #T_17992_row4_col6 {\n",
|
||||||
" background-color: #c13b82;\n",
|
" background-color: #c13b82;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col0 {\n",
|
"#T_17992_row4_col0 {\n",
|
||||||
" background-color: #35b779;\n",
|
" background-color: #35b779;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col1 {\n",
|
"#T_17992_row4_col1 {\n",
|
||||||
" background-color: #1f9f88;\n",
|
" background-color: #1f9f88;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col2 {\n",
|
"#T_17992_row4_col2 {\n",
|
||||||
" background-color: #81d34d;\n",
|
" background-color: #81d34d;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col3 {\n",
|
"#T_17992_row4_col3 {\n",
|
||||||
" background-color: #69cd5b;\n",
|
" background-color: #69cd5b;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col4 {\n",
|
"#T_17992_row4_col4 {\n",
|
||||||
" background-color: #b83289;\n",
|
" background-color: #b83289;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col5, #T_98a81_row5_col7 {\n",
|
"#T_17992_row4_col5, #T_17992_row5_col7 {\n",
|
||||||
" background-color: #aa2395;\n",
|
" background-color: #aa2395;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row4_col7 {\n",
|
"#T_17992_row4_col7 {\n",
|
||||||
" background-color: #b6308b;\n",
|
" background-color: #b6308b;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col0 {\n",
|
"#T_17992_row5_col0 {\n",
|
||||||
" background-color: #21a585;\n",
|
" background-color: #21a585;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col1 {\n",
|
"#T_17992_row5_col1 {\n",
|
||||||
" background-color: #21918c;\n",
|
" background-color: #21918c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col2 {\n",
|
"#T_17992_row5_col2 {\n",
|
||||||
" background-color: #73d056;\n",
|
" background-color: #73d056;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col3 {\n",
|
"#T_17992_row5_col3 {\n",
|
||||||
" background-color: #54c568;\n",
|
" background-color: #54c568;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col4 {\n",
|
"#T_17992_row5_col4 {\n",
|
||||||
" background-color: #a82296;\n",
|
" background-color: #a82296;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row5_col5 {\n",
|
"#T_17992_row5_col5 {\n",
|
||||||
" background-color: #99159f;\n",
|
" background-color: #99159f;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col0, #T_98a81_row6_col1, #T_98a81_row7_col2, #T_98a81_row7_col3 {\n",
|
"#T_17992_row6_col0, #T_17992_row6_col1, #T_17992_row7_col2, #T_17992_row7_col3 {\n",
|
||||||
" background-color: #26818e;\n",
|
" background-color: #26818e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col2 {\n",
|
"#T_17992_row6_col2 {\n",
|
||||||
" background-color: #22a785;\n",
|
" background-color: #22a785;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col3 {\n",
|
"#T_17992_row6_col3 {\n",
|
||||||
" background-color: #23a983;\n",
|
" background-color: #23a983;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col4 {\n",
|
"#T_17992_row6_col4 {\n",
|
||||||
" background-color: #5c01a6;\n",
|
" background-color: #5c01a6;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col5 {\n",
|
"#T_17992_row6_col5 {\n",
|
||||||
" background-color: #6c00a8;\n",
|
" background-color: #6c00a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col6 {\n",
|
"#T_17992_row6_col6 {\n",
|
||||||
" background-color: #7501a8;\n",
|
" background-color: #7501a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row6_col7 {\n",
|
"#T_17992_row6_col7 {\n",
|
||||||
" background-color: #8104a7;\n",
|
" background-color: #8104a7;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row7_col0 {\n",
|
"#T_17992_row7_col0 {\n",
|
||||||
" background-color: #3bbb75;\n",
|
" background-color: #3bbb75;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row7_col1 {\n",
|
"#T_17992_row7_col1 {\n",
|
||||||
" background-color: #34b679;\n",
|
" background-color: #34b679;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_98a81_row7_col4, #T_98a81_row7_col5, #T_98a81_row7_col6, #T_98a81_row7_col7 {\n",
|
"#T_17992_row7_col4, #T_17992_row7_col5, #T_17992_row7_col6, #T_17992_row7_col7 {\n",
|
||||||
" background-color: #4e02a2;\n",
|
" background-color: #4e02a2;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"</style>\n",
|
"</style>\n",
|
||||||
"<table id=\"T_98a81\">\n",
|
"<table id=\"T_17992\">\n",
|
||||||
" <thead>\n",
|
" <thead>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th class=\"blank level0\" > </th>\n",
|
" <th class=\"blank level0\" > </th>\n",
|
||||||
" <th id=\"T_98a81_level0_col0\" class=\"col_heading level0 col0\" >Precision_train</th>\n",
|
" <th id=\"T_17992_level0_col0\" class=\"col_heading level0 col0\" >Precision_train</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col1\" class=\"col_heading level0 col1\" >Precision_test</th>\n",
|
" <th id=\"T_17992_level0_col1\" class=\"col_heading level0 col1\" >Precision_test</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col2\" class=\"col_heading level0 col2\" >Recall_train</th>\n",
|
" <th id=\"T_17992_level0_col2\" class=\"col_heading level0 col2\" >Recall_train</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col3\" class=\"col_heading level0 col3\" >Recall_test</th>\n",
|
" <th id=\"T_17992_level0_col3\" class=\"col_heading level0 col3\" >Recall_test</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col4\" class=\"col_heading level0 col4\" >Accuracy_train</th>\n",
|
" <th id=\"T_17992_level0_col4\" class=\"col_heading level0 col4\" >Accuracy_train</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col5\" class=\"col_heading level0 col5\" >Accuracy_test</th>\n",
|
" <th id=\"T_17992_level0_col5\" class=\"col_heading level0 col5\" >Accuracy_test</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col6\" class=\"col_heading level0 col6\" >F1_train</th>\n",
|
" <th id=\"T_17992_level0_col6\" class=\"col_heading level0 col6\" >F1_train</th>\n",
|
||||||
" <th id=\"T_98a81_level0_col7\" class=\"col_heading level0 col7\" >F1_test</th>\n",
|
" <th id=\"T_17992_level0_col7\" class=\"col_heading level0 col7\" >F1_test</th>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </thead>\n",
|
" </thead>\n",
|
||||||
" <tbody>\n",
|
" <tbody>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row0\" class=\"row_heading level0 row0\" >gradient_boosting</th>\n",
|
" <th id=\"T_17992_level0_row0\" class=\"row_heading level0 row0\" >gradient_boosting</th>\n",
|
||||||
" <td id=\"T_98a81_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
|
" <td id=\"T_17992_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col1\" class=\"data row0 col1\" >0.982609</td>\n",
|
" <td id=\"T_17992_row0_col1\" class=\"data row0 col1\" >0.982609</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col2\" class=\"data row0 col2\" >1.000000</td>\n",
|
" <td id=\"T_17992_row0_col2\" class=\"data row0 col2\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col3\" class=\"data row0 col3\" >1.000000</td>\n",
|
" <td id=\"T_17992_row0_col3\" class=\"data row0 col3\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col4\" class=\"data row0 col4\" >1.000000</td>\n",
|
" <td id=\"T_17992_row0_col4\" class=\"data row0 col4\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col5\" class=\"data row0 col5\" >0.996396</td>\n",
|
" <td id=\"T_17992_row0_col5\" class=\"data row0 col5\" >0.996396</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col6\" class=\"data row0 col6\" >1.000000</td>\n",
|
" <td id=\"T_17992_row0_col6\" class=\"data row0 col6\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row0_col7\" class=\"data row0 col7\" >0.991228</td>\n",
|
" <td id=\"T_17992_row0_col7\" class=\"data row0 col7\" >0.991228</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row1\" class=\"row_heading level0 row1\" >decision_tree</th>\n",
|
" <th id=\"T_17992_level0_row1\" class=\"row_heading level0 row1\" >decision_tree</th>\n",
|
||||||
" <td id=\"T_98a81_row1_col0\" class=\"data row1 col0\" >0.976035</td>\n",
|
" <td id=\"T_17992_row1_col0\" class=\"data row1 col0\" >0.976035</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col1\" class=\"data row1 col1\" >0.956522</td>\n",
|
" <td id=\"T_17992_row1_col1\" class=\"data row1 col1\" >0.956522</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col2\" class=\"data row1 col2\" >0.993348</td>\n",
|
" <td id=\"T_17992_row1_col2\" class=\"data row1 col2\" >0.993348</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col3\" class=\"data row1 col3\" >0.973451</td>\n",
|
" <td id=\"T_17992_row1_col3\" class=\"data row1 col3\" >0.973451</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col4\" class=\"data row1 col4\" >0.993685</td>\n",
|
" <td id=\"T_17992_row1_col4\" class=\"data row1 col4\" >0.993685</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col5\" class=\"data row1 col5\" >0.985586</td>\n",
|
" <td id=\"T_17992_row1_col5\" class=\"data row1 col5\" >0.985586</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col6\" class=\"data row1 col6\" >0.984615</td>\n",
|
" <td id=\"T_17992_row1_col6\" class=\"data row1 col6\" >0.984615</td>\n",
|
||||||
" <td id=\"T_98a81_row1_col7\" class=\"data row1 col7\" >0.964912</td>\n",
|
" <td id=\"T_17992_row1_col7\" class=\"data row1 col7\" >0.964912</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row2\" class=\"row_heading level0 row2\" >random_forest</th>\n",
|
" <th id=\"T_17992_level0_row2\" class=\"row_heading level0 row2\" >random_forest</th>\n",
|
||||||
" <td id=\"T_98a81_row2_col0\" class=\"data row2 col0\" >0.995585</td>\n",
|
" <td id=\"T_17992_row2_col0\" class=\"data row2 col0\" >0.995585</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col1\" class=\"data row2 col1\" >0.948718</td>\n",
|
" <td id=\"T_17992_row2_col1\" class=\"data row2 col1\" >0.948718</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
|
" <td id=\"T_17992_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col3\" class=\"data row2 col3\" >0.982301</td>\n",
|
" <td id=\"T_17992_row2_col3\" class=\"data row2 col3\" >0.982301</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col4\" class=\"data row2 col4\" >0.999098</td>\n",
|
" <td id=\"T_17992_row2_col4\" class=\"data row2 col4\" >0.999098</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col5\" class=\"data row2 col5\" >0.985586</td>\n",
|
" <td id=\"T_17992_row2_col5\" class=\"data row2 col5\" >0.985586</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col6\" class=\"data row2 col6\" >0.997788</td>\n",
|
" <td id=\"T_17992_row2_col6\" class=\"data row2 col6\" >0.997788</td>\n",
|
||||||
" <td id=\"T_98a81_row2_col7\" class=\"data row2 col7\" >0.965217</td>\n",
|
" <td id=\"T_17992_row2_col7\" class=\"data row2 col7\" >0.965217</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row3\" class=\"row_heading level0 row3\" >ridge</th>\n",
|
" <th id=\"T_17992_level0_row3\" class=\"row_heading level0 row3\" >ridge</th>\n",
|
||||||
" <td id=\"T_98a81_row3_col0\" class=\"data row3 col0\" >0.846154</td>\n",
|
" <td id=\"T_17992_row3_col0\" class=\"data row3 col0\" >0.846154</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col1\" class=\"data row3 col1\" >0.837037</td>\n",
|
" <td id=\"T_17992_row3_col1\" class=\"data row3 col1\" >0.837037</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col2\" class=\"data row3 col2\" >1.000000</td>\n",
|
" <td id=\"T_17992_row3_col2\" class=\"data row3 col2\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
|
" <td id=\"T_17992_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col4\" class=\"data row3 col4\" >0.963013</td>\n",
|
" <td id=\"T_17992_row3_col4\" class=\"data row3 col4\" >0.963013</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col5\" class=\"data row3 col5\" >0.960360</td>\n",
|
" <td id=\"T_17992_row3_col5\" class=\"data row3 col5\" >0.960360</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col6\" class=\"data row3 col6\" >0.916667</td>\n",
|
" <td id=\"T_17992_row3_col6\" class=\"data row3 col6\" >0.916667</td>\n",
|
||||||
" <td id=\"T_98a81_row3_col7\" class=\"data row3 col7\" >0.911290</td>\n",
|
" <td id=\"T_17992_row3_col7\" class=\"data row3 col7\" >0.911290</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row4\" class=\"row_heading level0 row4\" >knn</th>\n",
|
" <th id=\"T_17992_level0_row4\" class=\"row_heading level0 row4\" >knn</th>\n",
|
||||||
" <td id=\"T_98a81_row4_col0\" class=\"data row4 col0\" >0.903846</td>\n",
|
" <td id=\"T_17992_row4_col0\" class=\"data row4 col0\" >0.903846</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col1\" class=\"data row4 col1\" >0.870690</td>\n",
|
" <td id=\"T_17992_row4_col1\" class=\"data row4 col1\" >0.870690</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col2\" class=\"data row4 col2\" >0.937916</td>\n",
|
" <td id=\"T_17992_row4_col2\" class=\"data row4 col2\" >0.937916</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col3\" class=\"data row4 col3\" >0.893805</td>\n",
|
" <td id=\"T_17992_row4_col3\" class=\"data row4 col3\" >0.893805</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col4\" class=\"data row4 col4\" >0.967073</td>\n",
|
" <td id=\"T_17992_row4_col4\" class=\"data row4 col4\" >0.967073</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col5\" class=\"data row4 col5\" >0.951351</td>\n",
|
" <td id=\"T_17992_row4_col5\" class=\"data row4 col5\" >0.951351</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col6\" class=\"data row4 col6\" >0.920566</td>\n",
|
" <td id=\"T_17992_row4_col6\" class=\"data row4 col6\" >0.920566</td>\n",
|
||||||
" <td id=\"T_98a81_row4_col7\" class=\"data row4 col7\" >0.882096</td>\n",
|
" <td id=\"T_17992_row4_col7\" class=\"data row4 col7\" >0.882096</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row5\" class=\"row_heading level0 row5\" >logistic</th>\n",
|
" <th id=\"T_17992_level0_row5\" class=\"row_heading level0 row5\" >logistic</th>\n",
|
||||||
" <td id=\"T_98a81_row5_col0\" class=\"data row5 col0\" >0.867368</td>\n",
|
" <td id=\"T_17992_row5_col0\" class=\"data row5 col0\" >0.867368</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col1\" class=\"data row5 col1\" >0.849558</td>\n",
|
" <td id=\"T_17992_row5_col1\" class=\"data row5 col1\" >0.849558</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col2\" class=\"data row5 col2\" >0.913525</td>\n",
|
" <td id=\"T_17992_row5_col2\" class=\"data row5 col2\" >0.913525</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col3\" class=\"data row5 col3\" >0.849558</td>\n",
|
" <td id=\"T_17992_row5_col3\" class=\"data row5 col3\" >0.849558</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col4\" class=\"data row5 col4\" >0.953992</td>\n",
|
" <td id=\"T_17992_row5_col4\" class=\"data row5 col4\" >0.953992</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col5\" class=\"data row5 col5\" >0.938739</td>\n",
|
" <td id=\"T_17992_row5_col5\" class=\"data row5 col5\" >0.938739</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col6\" class=\"data row5 col6\" >0.889849</td>\n",
|
" <td id=\"T_17992_row5_col6\" class=\"data row5 col6\" >0.889849</td>\n",
|
||||||
" <td id=\"T_98a81_row5_col7\" class=\"data row5 col7\" >0.849558</td>\n",
|
" <td id=\"T_17992_row5_col7\" class=\"data row5 col7\" >0.849558</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row6\" class=\"row_heading level0 row6\" >naive_bayes</th>\n",
|
" <th id=\"T_17992_level0_row6\" class=\"row_heading level0 row6\" >naive_bayes</th>\n",
|
||||||
" <td id=\"T_98a81_row6_col0\" class=\"data row6 col0\" >0.794045</td>\n",
|
" <td id=\"T_17992_row6_col0\" class=\"data row6 col0\" >0.794045</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col1\" class=\"data row6 col1\" >0.824742</td>\n",
|
" <td id=\"T_17992_row6_col1\" class=\"data row6 col1\" >0.824742</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col2\" class=\"data row6 col2\" >0.709534</td>\n",
|
" <td id=\"T_17992_row6_col2\" class=\"data row6 col2\" >0.709534</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col3\" class=\"data row6 col3\" >0.707965</td>\n",
|
" <td id=\"T_17992_row6_col3\" class=\"data row6 col3\" >0.707965</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col4\" class=\"data row6 col4\" >0.903473</td>\n",
|
" <td id=\"T_17992_row6_col4\" class=\"data row6 col4\" >0.903473</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col5\" class=\"data row6 col5\" >0.909910</td>\n",
|
" <td id=\"T_17992_row6_col5\" class=\"data row6 col5\" >0.909910</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col6\" class=\"data row6 col6\" >0.749415</td>\n",
|
" <td id=\"T_17992_row6_col6\" class=\"data row6 col6\" >0.749415</td>\n",
|
||||||
" <td id=\"T_98a81_row6_col7\" class=\"data row6 col7\" >0.761905</td>\n",
|
" <td id=\"T_17992_row6_col7\" class=\"data row6 col7\" >0.761905</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_98a81_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
" <th id=\"T_17992_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
||||||
" <td id=\"T_98a81_row7_col0\" class=\"data row7 col0\" >0.910112</td>\n",
|
" <td id=\"T_17992_row7_col0\" class=\"data row7 col0\" >0.910112</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col1\" class=\"data row7 col1\" >0.907692</td>\n",
|
" <td id=\"T_17992_row7_col1\" class=\"data row7 col1\" >0.907692</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col2\" class=\"data row7 col2\" >0.538803</td>\n",
|
" <td id=\"T_17992_row7_col2\" class=\"data row7 col2\" >0.538803</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col3\" class=\"data row7 col3\" >0.522124</td>\n",
|
" <td id=\"T_17992_row7_col3\" class=\"data row7 col3\" >0.522124</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col4\" class=\"data row7 col4\" >0.895354</td>\n",
|
" <td id=\"T_17992_row7_col4\" class=\"data row7 col4\" >0.895354</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col5\" class=\"data row7 col5\" >0.891892</td>\n",
|
" <td id=\"T_17992_row7_col5\" class=\"data row7 col5\" >0.891892</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col6\" class=\"data row7 col6\" >0.676880</td>\n",
|
" <td id=\"T_17992_row7_col6\" class=\"data row7 col6\" >0.676880</td>\n",
|
||||||
" <td id=\"T_98a81_row7_col7\" class=\"data row7 col7\" >0.662921</td>\n",
|
" <td id=\"T_17992_row7_col7\" class=\"data row7 col7\" >0.662921</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </tbody>\n",
|
" </tbody>\n",
|
||||||
"</table>\n"
|
"</table>\n"
|
||||||
],
|
],
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"<pandas.io.formats.style.Styler at 0x2464b71fd10>"
|
"<pandas.io.formats.style.Styler at 0x21de793ddc0>"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 30,
|
"execution_count": 9,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -1458,214 +1458,214 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 31,
|
"execution_count": 10,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/html": [
|
"text/html": [
|
||||||
"<style type=\"text/css\">\n",
|
"<style type=\"text/css\">\n",
|
||||||
"#T_fd909_row0_col0, #T_fd909_row2_col0 {\n",
|
"#T_ea44f_row0_col0, #T_ea44f_row2_col0 {\n",
|
||||||
" background-color: #8bd646;\n",
|
" background-color: #8bd646;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row0_col1, #T_fd909_row2_col1 {\n",
|
"#T_ea44f_row0_col1, #T_ea44f_row2_col1 {\n",
|
||||||
" background-color: #90d743;\n",
|
" background-color: #90d743;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row0_col2, #T_fd909_row1_col3, #T_fd909_row1_col4 {\n",
|
"#T_ea44f_row0_col2, #T_ea44f_row1_col3, #T_ea44f_row1_col4 {\n",
|
||||||
" background-color: #da5a6a;\n",
|
" background-color: #da5a6a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row0_col3, #T_fd909_row2_col3 {\n",
|
"#T_ea44f_row0_col3, #T_ea44f_row2_col3 {\n",
|
||||||
" background-color: #d24f71;\n",
|
" background-color: #d24f71;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row0_col4, #T_fd909_row2_col4 {\n",
|
"#T_ea44f_row0_col4, #T_ea44f_row2_col4 {\n",
|
||||||
" background-color: #d14e72;\n",
|
" background-color: #d14e72;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row1_col0, #T_fd909_row1_col1 {\n",
|
"#T_ea44f_row1_col0, #T_ea44f_row1_col1 {\n",
|
||||||
" background-color: #a8db34;\n",
|
" background-color: #a8db34;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row1_col2 {\n",
|
"#T_ea44f_row1_col2 {\n",
|
||||||
" background-color: #d7566c;\n",
|
" background-color: #d7566c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row2_col2 {\n",
|
"#T_ea44f_row2_col2 {\n",
|
||||||
" background-color: #cf4c74;\n",
|
" background-color: #cf4c74;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row3_col0, #T_fd909_row5_col1 {\n",
|
"#T_ea44f_row3_col0, #T_ea44f_row5_col1 {\n",
|
||||||
" background-color: #3bbb75;\n",
|
" background-color: #3bbb75;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row3_col1 {\n",
|
"#T_ea44f_row3_col1 {\n",
|
||||||
" background-color: #50c46a;\n",
|
" background-color: #50c46a;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row3_col2 {\n",
|
"#T_ea44f_row3_col2 {\n",
|
||||||
" background-color: #bc3587;\n",
|
" background-color: #bc3587;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row3_col3 {\n",
|
"#T_ea44f_row3_col3 {\n",
|
||||||
" background-color: #b32c8e;\n",
|
" background-color: #b32c8e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row3_col4 {\n",
|
"#T_ea44f_row3_col4 {\n",
|
||||||
" background-color: #b02991;\n",
|
" background-color: #b02991;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row4_col0 {\n",
|
"#T_ea44f_row4_col0 {\n",
|
||||||
" background-color: #4ec36b;\n",
|
" background-color: #4ec36b;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row4_col1 {\n",
|
"#T_ea44f_row4_col1 {\n",
|
||||||
" background-color: #65cb5e;\n",
|
" background-color: #65cb5e;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row4_col2 {\n",
|
"#T_ea44f_row4_col2 {\n",
|
||||||
" background-color: #99159f;\n",
|
" background-color: #99159f;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row4_col3 {\n",
|
"#T_ea44f_row4_col3 {\n",
|
||||||
" background-color: #be3885;\n",
|
" background-color: #be3885;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row4_col4 {\n",
|
"#T_ea44f_row4_col4 {\n",
|
||||||
" background-color: #bd3786;\n",
|
" background-color: #bd3786;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row5_col0 {\n",
|
"#T_ea44f_row5_col0 {\n",
|
||||||
" background-color: #29af7f;\n",
|
" background-color: #29af7f;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row5_col2 {\n",
|
"#T_ea44f_row5_col2 {\n",
|
||||||
" background-color: #9613a1;\n",
|
" background-color: #9613a1;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row5_col3 {\n",
|
"#T_ea44f_row5_col3 {\n",
|
||||||
" background-color: #a62098;\n",
|
" background-color: #a62098;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row5_col4 {\n",
|
"#T_ea44f_row5_col4 {\n",
|
||||||
" background-color: #a01a9c;\n",
|
" background-color: #a01a9c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row6_col0 {\n",
|
"#T_ea44f_row6_col0 {\n",
|
||||||
" background-color: #20928c;\n",
|
" background-color: #20928c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row6_col1 {\n",
|
"#T_ea44f_row6_col1 {\n",
|
||||||
" background-color: #1fa088;\n",
|
" background-color: #1fa088;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row6_col2 {\n",
|
"#T_ea44f_row6_col2 {\n",
|
||||||
" background-color: #7401a8;\n",
|
" background-color: #7401a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row6_col3 {\n",
|
"#T_ea44f_row6_col3 {\n",
|
||||||
" background-color: #7d03a8;\n",
|
" background-color: #7d03a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row6_col4 {\n",
|
"#T_ea44f_row6_col4 {\n",
|
||||||
" background-color: #7201a8;\n",
|
" background-color: #7201a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row7_col0, #T_fd909_row7_col1 {\n",
|
"#T_ea44f_row7_col0, #T_ea44f_row7_col1 {\n",
|
||||||
" background-color: #26818e;\n",
|
" background-color: #26818e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_fd909_row7_col2, #T_fd909_row7_col3, #T_fd909_row7_col4 {\n",
|
"#T_ea44f_row7_col2, #T_ea44f_row7_col3, #T_ea44f_row7_col4 {\n",
|
||||||
" background-color: #4e02a2;\n",
|
" background-color: #4e02a2;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"</style>\n",
|
"</style>\n",
|
||||||
"<table id=\"T_fd909\">\n",
|
"<table id=\"T_ea44f\">\n",
|
||||||
" <thead>\n",
|
" <thead>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th class=\"blank level0\" > </th>\n",
|
" <th class=\"blank level0\" > </th>\n",
|
||||||
" <th id=\"T_fd909_level0_col0\" class=\"col_heading level0 col0\" >Accuracy_test</th>\n",
|
" <th id=\"T_ea44f_level0_col0\" class=\"col_heading level0 col0\" >Accuracy_test</th>\n",
|
||||||
" <th id=\"T_fd909_level0_col1\" class=\"col_heading level0 col1\" >F1_test</th>\n",
|
" <th id=\"T_ea44f_level0_col1\" class=\"col_heading level0 col1\" >F1_test</th>\n",
|
||||||
" <th id=\"T_fd909_level0_col2\" class=\"col_heading level0 col2\" >ROC_AUC_test</th>\n",
|
" <th id=\"T_ea44f_level0_col2\" class=\"col_heading level0 col2\" >ROC_AUC_test</th>\n",
|
||||||
" <th id=\"T_fd909_level0_col3\" class=\"col_heading level0 col3\" >Cohen_kappa_test</th>\n",
|
" <th id=\"T_ea44f_level0_col3\" class=\"col_heading level0 col3\" >Cohen_kappa_test</th>\n",
|
||||||
" <th id=\"T_fd909_level0_col4\" class=\"col_heading level0 col4\" >MCC_test</th>\n",
|
" <th id=\"T_ea44f_level0_col4\" class=\"col_heading level0 col4\" >MCC_test</th>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </thead>\n",
|
" </thead>\n",
|
||||||
" <tbody>\n",
|
" <tbody>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row0\" class=\"row_heading level0 row0\" >random_forest</th>\n",
|
" <th id=\"T_ea44f_level0_row0\" class=\"row_heading level0 row0\" >random_forest</th>\n",
|
||||||
" <td id=\"T_fd909_row0_col0\" class=\"data row0 col0\" >0.985586</td>\n",
|
" <td id=\"T_ea44f_row0_col0\" class=\"data row0 col0\" >0.985586</td>\n",
|
||||||
" <td id=\"T_fd909_row0_col1\" class=\"data row0 col1\" >0.965217</td>\n",
|
" <td id=\"T_ea44f_row0_col1\" class=\"data row0 col1\" >0.965217</td>\n",
|
||||||
" <td id=\"T_fd909_row0_col2\" class=\"data row0 col2\" >0.999039</td>\n",
|
" <td id=\"T_ea44f_row0_col2\" class=\"data row0 col2\" >0.999039</td>\n",
|
||||||
" <td id=\"T_fd909_row0_col3\" class=\"data row0 col3\" >0.956130</td>\n",
|
" <td id=\"T_ea44f_row0_col3\" class=\"data row0 col3\" >0.956130</td>\n",
|
||||||
" <td id=\"T_fd909_row0_col4\" class=\"data row0 col4\" >0.956360</td>\n",
|
" <td id=\"T_ea44f_row0_col4\" class=\"data row0 col4\" >0.956360</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row1\" class=\"row_heading level0 row1\" >gradient_boosting</th>\n",
|
" <th id=\"T_ea44f_level0_row1\" class=\"row_heading level0 row1\" >gradient_boosting</th>\n",
|
||||||
" <td id=\"T_fd909_row1_col0\" class=\"data row1 col0\" >0.996396</td>\n",
|
" <td id=\"T_ea44f_row1_col0\" class=\"data row1 col0\" >0.996396</td>\n",
|
||||||
" <td id=\"T_fd909_row1_col1\" class=\"data row1 col1\" >0.991228</td>\n",
|
" <td id=\"T_ea44f_row1_col1\" class=\"data row1 col1\" >0.991228</td>\n",
|
||||||
" <td id=\"T_fd909_row1_col2\" class=\"data row1 col2\" >0.998118</td>\n",
|
" <td id=\"T_ea44f_row1_col2\" class=\"data row1 col2\" >0.998118</td>\n",
|
||||||
" <td id=\"T_fd909_row1_col3\" class=\"data row1 col3\" >0.988961</td>\n",
|
" <td id=\"T_ea44f_row1_col3\" class=\"data row1 col3\" >0.988961</td>\n",
|
||||||
" <td id=\"T_fd909_row1_col4\" class=\"data row1 col4\" >0.989021</td>\n",
|
" <td id=\"T_ea44f_row1_col4\" class=\"data row1 col4\" >0.989021</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row2\" class=\"row_heading level0 row2\" >decision_tree</th>\n",
|
" <th id=\"T_ea44f_level0_row2\" class=\"row_heading level0 row2\" >decision_tree</th>\n",
|
||||||
" <td id=\"T_fd909_row2_col0\" class=\"data row2 col0\" >0.985586</td>\n",
|
" <td id=\"T_ea44f_row2_col0\" class=\"data row2 col0\" >0.985586</td>\n",
|
||||||
" <td id=\"T_fd909_row2_col1\" class=\"data row2 col1\" >0.964912</td>\n",
|
" <td id=\"T_ea44f_row2_col1\" class=\"data row2 col1\" >0.964912</td>\n",
|
||||||
" <td id=\"T_fd909_row2_col2\" class=\"data row2 col2\" >0.995745</td>\n",
|
" <td id=\"T_ea44f_row2_col2\" class=\"data row2 col2\" >0.995745</td>\n",
|
||||||
" <td id=\"T_fd909_row2_col3\" class=\"data row2 col3\" >0.955843</td>\n",
|
" <td id=\"T_ea44f_row2_col3\" class=\"data row2 col3\" >0.955843</td>\n",
|
||||||
" <td id=\"T_fd909_row2_col4\" class=\"data row2 col4\" >0.955901</td>\n",
|
" <td id=\"T_ea44f_row2_col4\" class=\"data row2 col4\" >0.955901</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row3\" class=\"row_heading level0 row3\" >knn</th>\n",
|
" <th id=\"T_ea44f_level0_row3\" class=\"row_heading level0 row3\" >knn</th>\n",
|
||||||
" <td id=\"T_fd909_row3_col0\" class=\"data row3 col0\" >0.951351</td>\n",
|
" <td id=\"T_ea44f_row3_col0\" class=\"data row3 col0\" >0.951351</td>\n",
|
||||||
" <td id=\"T_fd909_row3_col1\" class=\"data row3 col1\" >0.882096</td>\n",
|
" <td id=\"T_ea44f_row3_col1\" class=\"data row3 col1\" >0.882096</td>\n",
|
||||||
" <td id=\"T_fd909_row3_col2\" class=\"data row3 col2\" >0.990049</td>\n",
|
" <td id=\"T_ea44f_row3_col2\" class=\"data row3 col2\" >0.990049</td>\n",
|
||||||
" <td id=\"T_fd909_row3_col3\" class=\"data row3 col3\" >0.851456</td>\n",
|
" <td id=\"T_ea44f_row3_col3\" class=\"data row3 col3\" >0.851456</td>\n",
|
||||||
" <td id=\"T_fd909_row3_col4\" class=\"data row3 col4\" >0.851572</td>\n",
|
" <td id=\"T_ea44f_row3_col4\" class=\"data row3 col4\" >0.851572</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row4\" class=\"row_heading level0 row4\" >ridge</th>\n",
|
" <th id=\"T_ea44f_level0_row4\" class=\"row_heading level0 row4\" >ridge</th>\n",
|
||||||
" <td id=\"T_fd909_row4_col0\" class=\"data row4 col0\" >0.960360</td>\n",
|
" <td id=\"T_ea44f_row4_col0\" class=\"data row4 col0\" >0.960360</td>\n",
|
||||||
" <td id=\"T_fd909_row4_col1\" class=\"data row4 col1\" >0.911290</td>\n",
|
" <td id=\"T_ea44f_row4_col1\" class=\"data row4 col1\" >0.911290</td>\n",
|
||||||
" <td id=\"T_fd909_row4_col2\" class=\"data row4 col2\" >0.982001</td>\n",
|
" <td id=\"T_ea44f_row4_col2\" class=\"data row4 col2\" >0.982001</td>\n",
|
||||||
" <td id=\"T_fd909_row4_col3\" class=\"data row4 col3\" >0.886026</td>\n",
|
" <td id=\"T_ea44f_row4_col3\" class=\"data row4 col3\" >0.886026</td>\n",
|
||||||
" <td id=\"T_fd909_row4_col4\" class=\"data row4 col4\" >0.891838</td>\n",
|
" <td id=\"T_ea44f_row4_col4\" class=\"data row4 col4\" >0.891838</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row5\" class=\"row_heading level0 row5\" >logistic</th>\n",
|
" <th id=\"T_ea44f_level0_row5\" class=\"row_heading level0 row5\" >logistic</th>\n",
|
||||||
" <td id=\"T_fd909_row5_col0\" class=\"data row5 col0\" >0.938739</td>\n",
|
" <td id=\"T_ea44f_row5_col0\" class=\"data row5 col0\" >0.938739</td>\n",
|
||||||
" <td id=\"T_fd909_row5_col1\" class=\"data row5 col1\" >0.849558</td>\n",
|
" <td id=\"T_ea44f_row5_col1\" class=\"data row5 col1\" >0.849558</td>\n",
|
||||||
" <td id=\"T_fd909_row5_col2\" class=\"data row5 col2\" >0.981520</td>\n",
|
" <td id=\"T_ea44f_row5_col2\" class=\"data row5 col2\" >0.981520</td>\n",
|
||||||
" <td id=\"T_fd909_row5_col3\" class=\"data row5 col3\" >0.811096</td>\n",
|
" <td id=\"T_ea44f_row5_col3\" class=\"data row5 col3\" >0.811096</td>\n",
|
||||||
" <td id=\"T_fd909_row5_col4\" class=\"data row5 col4\" >0.811096</td>\n",
|
" <td id=\"T_ea44f_row5_col4\" class=\"data row5 col4\" >0.811096</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row6\" class=\"row_heading level0 row6\" >naive_bayes</th>\n",
|
" <th id=\"T_ea44f_level0_row6\" class=\"row_heading level0 row6\" >naive_bayes</th>\n",
|
||||||
" <td id=\"T_fd909_row6_col0\" class=\"data row6 col0\" >0.909910</td>\n",
|
" <td id=\"T_ea44f_row6_col0\" class=\"data row6 col0\" >0.909910</td>\n",
|
||||||
" <td id=\"T_fd909_row6_col1\" class=\"data row6 col1\" >0.761905</td>\n",
|
" <td id=\"T_ea44f_row6_col1\" class=\"data row6 col1\" >0.761905</td>\n",
|
||||||
" <td id=\"T_fd909_row6_col2\" class=\"data row6 col2\" >0.974813</td>\n",
|
" <td id=\"T_ea44f_row6_col2\" class=\"data row6 col2\" >0.974813</td>\n",
|
||||||
" <td id=\"T_fd909_row6_col3\" class=\"data row6 col3\" >0.706746</td>\n",
|
" <td id=\"T_ea44f_row6_col3\" class=\"data row6 col3\" >0.706746</td>\n",
|
||||||
" <td id=\"T_fd909_row6_col4\" class=\"data row6 col4\" >0.709879</td>\n",
|
" <td id=\"T_ea44f_row6_col4\" class=\"data row6 col4\" >0.709879</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_fd909_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
" <th id=\"T_ea44f_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
||||||
" <td id=\"T_fd909_row7_col0\" class=\"data row7 col0\" >0.891892</td>\n",
|
" <td id=\"T_ea44f_row7_col0\" class=\"data row7 col0\" >0.891892</td>\n",
|
||||||
" <td id=\"T_fd909_row7_col1\" class=\"data row7 col1\" >0.662921</td>\n",
|
" <td id=\"T_ea44f_row7_col1\" class=\"data row7 col1\" >0.662921</td>\n",
|
||||||
" <td id=\"T_fd909_row7_col2\" class=\"data row7 col2\" >0.968086</td>\n",
|
" <td id=\"T_ea44f_row7_col2\" class=\"data row7 col2\" >0.968086</td>\n",
|
||||||
" <td id=\"T_fd909_row7_col3\" class=\"data row7 col3\" >0.604043</td>\n",
|
" <td id=\"T_ea44f_row7_col3\" class=\"data row7 col3\" >0.604043</td>\n",
|
||||||
" <td id=\"T_fd909_row7_col4\" class=\"data row7 col4\" >0.636838</td>\n",
|
" <td id=\"T_ea44f_row7_col4\" class=\"data row7 col4\" >0.636838</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </tbody>\n",
|
" </tbody>\n",
|
||||||
"</table>\n"
|
"</table>\n"
|
||||||
],
|
],
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"<pandas.io.formats.style.Styler at 0x24665055160>"
|
"<pandas.io.formats.style.Styler at 0x21de8b38e60>"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 31,
|
"execution_count": 10,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -1702,7 +1702,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 32,
|
"execution_count": 11,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1730,7 +1730,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 34,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1806,7 +1806,7 @@
|
|||||||
"1969 32 1 female 23.65 1 0 southeast 17626.23951"
|
"1969 32 1 female 23.65 1 0 southeast 17626.23951"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 34,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -1838,7 +1838,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 46,
|
"execution_count": 13,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -2014,31 +2014,9 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 47,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [],
|
||||||
{
|
|
||||||
"name": "stderr",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"c:\\Users\\frenk\\OneDrive\\Рабочий стол\\MII_Salin_Oleg_PIbd-33\\.venv\\Lib\\site-packages\\numpy\\ma\\core.py:2881: RuntimeWarning: invalid value encountered in cast\n",
|
|
||||||
" _data = np.array(data, dtype=dtype, copy=copy,\n"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"{'model__criterion': 'entropy',\n",
|
|
||||||
" 'model__max_depth': 10,\n",
|
|
||||||
" 'model__max_features': 'log2',\n",
|
|
||||||
" 'model__n_estimators': 250}"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 47,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
"source": [
|
||||||
"from sklearn.model_selection import GridSearchCV\n",
|
"from sklearn.model_selection import GridSearchCV\n",
|
||||||
"\n",
|
"\n",
|
||||||
@ -2069,7 +2047,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 48,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -2111,7 +2089,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 49,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -2135,7 +2113,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 50,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -2251,7 +2229,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 51,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -2354,7 +2332,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 52,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
|
|||||||
166
lec4_reg.ipynb
166
lec4_reg.ipynb
@ -9,7 +9,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 74,
|
"execution_count": 2,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -212,7 +212,7 @@
|
|||||||
"[2772 rows x 9 columns]"
|
"[2772 rows x 9 columns]"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 74,
|
"execution_count": 2,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -255,7 +255,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 75,
|
"execution_count": 3,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -897,7 +897,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 76,
|
"execution_count": 4,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -952,7 +952,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 77,
|
"execution_count": 5,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
@ -985,7 +985,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 78,
|
"execution_count": 6,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1047,177 +1047,177 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 79,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/html": [
|
"text/html": [
|
||||||
"<style type=\"text/css\">\n",
|
"<style type=\"text/css\">\n",
|
||||||
"#T_995df_row0_col0, #T_995df_row0_col1 {\n",
|
"#T_3759d_row0_col0, #T_3759d_row0_col1 {\n",
|
||||||
" background-color: #26818e;\n",
|
" background-color: #26818e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row0_col2, #T_995df_row7_col3 {\n",
|
"#T_3759d_row0_col2, #T_3759d_row7_col3 {\n",
|
||||||
" background-color: #4e02a2;\n",
|
" background-color: #4e02a2;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row0_col3, #T_995df_row7_col2 {\n",
|
"#T_3759d_row0_col3, #T_3759d_row7_col2 {\n",
|
||||||
" background-color: #da5a6a;\n",
|
" background-color: #da5a6a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row1_col0 {\n",
|
"#T_3759d_row1_col0 {\n",
|
||||||
" background-color: #25838e;\n",
|
" background-color: #25838e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row1_col1 {\n",
|
"#T_3759d_row1_col1 {\n",
|
||||||
" background-color: #26828e;\n",
|
" background-color: #26828e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row1_col2 {\n",
|
"#T_3759d_row1_col2 {\n",
|
||||||
" background-color: #5102a3;\n",
|
" background-color: #5102a3;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row1_col3 {\n",
|
"#T_3759d_row1_col3 {\n",
|
||||||
" background-color: #d9586a;\n",
|
" background-color: #d9586a;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row2_col0 {\n",
|
"#T_3759d_row2_col0 {\n",
|
||||||
" background-color: #228b8d;\n",
|
" background-color: #228b8d;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row2_col1, #T_995df_row3_col1 {\n",
|
"#T_3759d_row2_col1, #T_3759d_row3_col1 {\n",
|
||||||
" background-color: #24878e;\n",
|
" background-color: #24878e;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row2_col2 {\n",
|
"#T_3759d_row2_col2 {\n",
|
||||||
" background-color: #6300a7;\n",
|
" background-color: #6300a7;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row2_col3, #T_995df_row3_col3 {\n",
|
"#T_3759d_row2_col3, #T_3759d_row3_col3 {\n",
|
||||||
" background-color: #d7566c;\n",
|
" background-color: #d7566c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row3_col0 {\n",
|
"#T_3759d_row3_col0 {\n",
|
||||||
" background-color: #228c8d;\n",
|
" background-color: #228c8d;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row3_col2 {\n",
|
"#T_3759d_row3_col2 {\n",
|
||||||
" background-color: #6400a7;\n",
|
" background-color: #6400a7;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row4_col0, #T_995df_row5_col0 {\n",
|
"#T_3759d_row4_col0, #T_3759d_row5_col0 {\n",
|
||||||
" background-color: #1f948c;\n",
|
" background-color: #1f948c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row4_col1, #T_995df_row5_col1 {\n",
|
"#T_3759d_row4_col1, #T_3759d_row5_col1 {\n",
|
||||||
" background-color: #21918c;\n",
|
" background-color: #21918c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row4_col2, #T_995df_row5_col2 {\n",
|
"#T_3759d_row4_col2, #T_3759d_row5_col2 {\n",
|
||||||
" background-color: #7e03a8;\n",
|
" background-color: #7e03a8;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row4_col3, #T_995df_row5_col3 {\n",
|
"#T_3759d_row4_col3, #T_3759d_row5_col3 {\n",
|
||||||
" background-color: #d35171;\n",
|
" background-color: #d35171;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row6_col0 {\n",
|
"#T_3759d_row6_col0 {\n",
|
||||||
" background-color: #20a486;\n",
|
" background-color: #20a486;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row6_col1 {\n",
|
"#T_3759d_row6_col1 {\n",
|
||||||
" background-color: #24aa83;\n",
|
" background-color: #24aa83;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row6_col2 {\n",
|
"#T_3759d_row6_col2 {\n",
|
||||||
" background-color: #a01a9c;\n",
|
" background-color: #a01a9c;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row6_col3 {\n",
|
"#T_3759d_row6_col3 {\n",
|
||||||
" background-color: #c13b82;\n",
|
" background-color: #c13b82;\n",
|
||||||
" color: #f1f1f1;\n",
|
" color: #f1f1f1;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"#T_995df_row7_col0, #T_995df_row7_col1 {\n",
|
"#T_3759d_row7_col0, #T_3759d_row7_col1 {\n",
|
||||||
" background-color: #a8db34;\n",
|
" background-color: #a8db34;\n",
|
||||||
" color: #000000;\n",
|
" color: #000000;\n",
|
||||||
"}\n",
|
"}\n",
|
||||||
"</style>\n",
|
"</style>\n",
|
||||||
"<table id=\"T_995df\">\n",
|
"<table id=\"T_3759d\">\n",
|
||||||
" <thead>\n",
|
" <thead>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th class=\"blank level0\" > </th>\n",
|
" <th class=\"blank level0\" > </th>\n",
|
||||||
" <th id=\"T_995df_level0_col0\" class=\"col_heading level0 col0\" >RMSE_train</th>\n",
|
" <th id=\"T_3759d_level0_col0\" class=\"col_heading level0 col0\" >RMSE_train</th>\n",
|
||||||
" <th id=\"T_995df_level0_col1\" class=\"col_heading level0 col1\" >RMSE_test</th>\n",
|
" <th id=\"T_3759d_level0_col1\" class=\"col_heading level0 col1\" >RMSE_test</th>\n",
|
||||||
" <th id=\"T_995df_level0_col2\" class=\"col_heading level0 col2\" >RMAE_test</th>\n",
|
" <th id=\"T_3759d_level0_col2\" class=\"col_heading level0 col2\" >RMAE_test</th>\n",
|
||||||
" <th id=\"T_995df_level0_col3\" class=\"col_heading level0 col3\" >R2_test</th>\n",
|
" <th id=\"T_3759d_level0_col3\" class=\"col_heading level0 col3\" >R2_test</th>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </thead>\n",
|
" </thead>\n",
|
||||||
" <tbody>\n",
|
" <tbody>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row0\" class=\"row_heading level0 row0\" >random_forest</th>\n",
|
" <th id=\"T_3759d_level0_row0\" class=\"row_heading level0 row0\" >random_forest</th>\n",
|
||||||
" <td id=\"T_995df_row0_col0\" class=\"data row0 col0\" >3221.469707</td>\n",
|
" <td id=\"T_3759d_row0_col0\" class=\"data row0 col0\" >3221.469707</td>\n",
|
||||||
" <td id=\"T_995df_row0_col1\" class=\"data row0 col1\" >3953.661053</td>\n",
|
" <td id=\"T_3759d_row0_col1\" class=\"data row0 col1\" >3953.661053</td>\n",
|
||||||
" <td id=\"T_995df_row0_col2\" class=\"data row0 col2\" >45.741609</td>\n",
|
" <td id=\"T_3759d_row0_col2\" class=\"data row0 col2\" >45.741609</td>\n",
|
||||||
" <td id=\"T_995df_row0_col3\" class=\"data row0 col3\" >0.901103</td>\n",
|
" <td id=\"T_3759d_row0_col3\" class=\"data row0 col3\" >0.901103</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row1\" class=\"row_heading level0 row1\" >decision_tree</th>\n",
|
" <th id=\"T_3759d_level0_row1\" class=\"row_heading level0 row1\" >decision_tree</th>\n",
|
||||||
" <td id=\"T_995df_row1_col0\" class=\"data row1 col0\" >3643.279193</td>\n",
|
" <td id=\"T_3759d_row1_col0\" class=\"data row1 col0\" >3643.279193</td>\n",
|
||||||
" <td id=\"T_995df_row1_col1\" class=\"data row1 col1\" >4288.040726</td>\n",
|
" <td id=\"T_3759d_row1_col1\" class=\"data row1 col1\" >4288.040726</td>\n",
|
||||||
" <td id=\"T_995df_row1_col2\" class=\"data row1 col2\" >47.359073</td>\n",
|
" <td id=\"T_3759d_row1_col2\" class=\"data row1 col2\" >47.359073</td>\n",
|
||||||
" <td id=\"T_995df_row1_col3\" class=\"data row1 col3\" >0.883668</td>\n",
|
" <td id=\"T_3759d_row1_col3\" class=\"data row1 col3\" >0.883668</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row2\" class=\"row_heading level0 row2\" >linear_poly</th>\n",
|
" <th id=\"T_3759d_level0_row2\" class=\"row_heading level0 row2\" >linear_poly</th>\n",
|
||||||
" <td id=\"T_995df_row2_col0\" class=\"data row2 col0\" >4731.024654</td>\n",
|
" <td id=\"T_3759d_row2_col0\" class=\"data row2 col0\" >4731.024654</td>\n",
|
||||||
" <td id=\"T_995df_row2_col1\" class=\"data row2 col1\" >4868.817371</td>\n",
|
" <td id=\"T_3759d_row2_col1\" class=\"data row2 col1\" >4868.817371</td>\n",
|
||||||
" <td id=\"T_995df_row2_col2\" class=\"data row2 col2\" >54.257745</td>\n",
|
" <td id=\"T_3759d_row2_col2\" class=\"data row2 col2\" >54.257745</td>\n",
|
||||||
" <td id=\"T_995df_row2_col3\" class=\"data row2 col3\" >0.850021</td>\n",
|
" <td id=\"T_3759d_row2_col3\" class=\"data row2 col3\" >0.850021</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row3\" class=\"row_heading level0 row3\" >linear_interact</th>\n",
|
" <th id=\"T_3759d_level0_row3\" class=\"row_heading level0 row3\" >linear_interact</th>\n",
|
||||||
" <td id=\"T_995df_row3_col0\" class=\"data row3 col0\" >4776.393716</td>\n",
|
" <td id=\"T_3759d_row3_col0\" class=\"data row3 col0\" >4776.393716</td>\n",
|
||||||
" <td id=\"T_995df_row3_col1\" class=\"data row3 col1\" >4938.699556</td>\n",
|
" <td id=\"T_3759d_row3_col1\" class=\"data row3 col1\" >4938.699556</td>\n",
|
||||||
" <td id=\"T_995df_row3_col2\" class=\"data row3 col2\" >54.641209</td>\n",
|
" <td id=\"T_3759d_row3_col2\" class=\"data row3 col2\" >54.641209</td>\n",
|
||||||
" <td id=\"T_995df_row3_col3\" class=\"data row3 col3\" >0.845685</td>\n",
|
" <td id=\"T_3759d_row3_col3\" class=\"data row3 col3\" >0.845685</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row4\" class=\"row_heading level0 row4\" >ridge</th>\n",
|
" <th id=\"T_3759d_level0_row4\" class=\"row_heading level0 row4\" >ridge</th>\n",
|
||||||
" <td id=\"T_995df_row4_col0\" class=\"data row4 col0\" >6028.427617</td>\n",
|
" <td id=\"T_3759d_row4_col0\" class=\"data row4 col0\" >6028.427617</td>\n",
|
||||||
" <td id=\"T_995df_row4_col1\" class=\"data row4 col1\" >6216.544081</td>\n",
|
" <td id=\"T_3759d_row4_col1\" class=\"data row4 col1\" >6216.544081</td>\n",
|
||||||
" <td id=\"T_995df_row4_col2\" class=\"data row4 col2\" >65.584948</td>\n",
|
" <td id=\"T_3759d_row4_col2\" class=\"data row4 col2\" >65.584948</td>\n",
|
||||||
" <td id=\"T_995df_row4_col3\" class=\"data row4 col3\" >0.755499</td>\n",
|
" <td id=\"T_3759d_row4_col3\" class=\"data row4 col3\" >0.755499</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row5\" class=\"row_heading level0 row5\" >linear</th>\n",
|
" <th id=\"T_3759d_level0_row5\" class=\"row_heading level0 row5\" >linear</th>\n",
|
||||||
" <td id=\"T_995df_row5_col0\" class=\"data row5 col0\" >6028.426993</td>\n",
|
" <td id=\"T_3759d_row5_col0\" class=\"data row5 col0\" >6028.426993</td>\n",
|
||||||
" <td id=\"T_995df_row5_col1\" class=\"data row5 col1\" >6216.588829</td>\n",
|
" <td id=\"T_3759d_row5_col1\" class=\"data row5 col1\" >6216.588829</td>\n",
|
||||||
" <td id=\"T_995df_row5_col2\" class=\"data row5 col2\" >65.580879</td>\n",
|
" <td id=\"T_3759d_row5_col2\" class=\"data row5 col2\" >65.580879</td>\n",
|
||||||
" <td id=\"T_995df_row5_col3\" class=\"data row5 col3\" >0.755496</td>\n",
|
" <td id=\"T_3759d_row5_col3\" class=\"data row5 col3\" >0.755496</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row6\" class=\"row_heading level0 row6\" >knn</th>\n",
|
" <th id=\"T_3759d_level0_row6\" class=\"row_heading level0 row6\" >knn</th>\n",
|
||||||
" <td id=\"T_995df_row6_col0\" class=\"data row6 col0\" >8230.959070</td>\n",
|
" <td id=\"T_3759d_row6_col0\" class=\"data row6 col0\" >8230.959070</td>\n",
|
||||||
" <td id=\"T_995df_row6_col1\" class=\"data row6 col1\" >9715.102581</td>\n",
|
" <td id=\"T_3759d_row6_col1\" class=\"data row6 col1\" >9715.102581</td>\n",
|
||||||
" <td id=\"T_995df_row6_col2\" class=\"data row6 col2\" >81.129201</td>\n",
|
" <td id=\"T_3759d_row6_col2\" class=\"data row6 col2\" >81.129201</td>\n",
|
||||||
" <td id=\"T_995df_row6_col3\" class=\"data row6 col3\" >0.402859</td>\n",
|
" <td id=\"T_3759d_row6_col3\" class=\"data row6 col3\" >0.402859</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" <tr>\n",
|
" <tr>\n",
|
||||||
" <th id=\"T_995df_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
" <th id=\"T_3759d_level0_row7\" class=\"row_heading level0 row7\" >mlp</th>\n",
|
||||||
" <td id=\"T_995df_row7_col0\" class=\"data row7 col0\" >17848.198895</td>\n",
|
" <td id=\"T_3759d_row7_col0\" class=\"data row7 col0\" >17848.198895</td>\n",
|
||||||
" <td id=\"T_995df_row7_col1\" class=\"data row7 col1\" >18518.275054</td>\n",
|
" <td id=\"T_3759d_row7_col1\" class=\"data row7 col1\" >18518.275054</td>\n",
|
||||||
" <td id=\"T_995df_row7_col2\" class=\"data row7 col2\" >116.605174</td>\n",
|
" <td id=\"T_3759d_row7_col2\" class=\"data row7 col2\" >116.605174</td>\n",
|
||||||
" <td id=\"T_995df_row7_col3\" class=\"data row7 col3\" >-1.169619</td>\n",
|
" <td id=\"T_3759d_row7_col3\" class=\"data row7 col3\" >-1.169619</td>\n",
|
||||||
" </tr>\n",
|
" </tr>\n",
|
||||||
" </tbody>\n",
|
" </tbody>\n",
|
||||||
"</table>\n"
|
"</table>\n"
|
||||||
],
|
],
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"<pandas.io.formats.style.Styler at 0x1d2bcd71160>"
|
"<pandas.io.formats.style.Styler at 0x203e1a15460>"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 79,
|
"execution_count": 7,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -1226,7 +1226,7 @@
|
|||||||
"reg_metrics = pd.DataFrame.from_dict(models, \"index\")[\n",
|
"reg_metrics = pd.DataFrame.from_dict(models, \"index\")[\n",
|
||||||
" [\"RMSE_train\", \"RMSE_test\", \"RMAE_test\", \"R2_test\"]\n",
|
" [\"RMSE_train\", \"RMSE_test\", \"RMAE_test\", \"R2_test\"]\n",
|
||||||
"]\n",
|
"]\n",
|
||||||
"reg_metrics.sort_values(by=\"RMSE_test\").style.background_gradient(\n",
|
"reg_metrics.sort_values(by=\"RMSE_test\").style.background_gradient( # type: ignore\n",
|
||||||
" cmap=\"viridis\", low=1, high=0.3, subset=[\"RMSE_train\", \"RMSE_test\"]\n",
|
" cmap=\"viridis\", low=1, high=0.3, subset=[\"RMSE_train\", \"RMSE_test\"]\n",
|
||||||
").background_gradient(cmap=\"plasma\", low=0.3, high=1, subset=[\"RMAE_test\", \"R2_test\"])"
|
").background_gradient(cmap=\"plasma\", low=0.3, high=1, subset=[\"RMAE_test\", \"R2_test\"])"
|
||||||
]
|
]
|
||||||
@ -1247,7 +1247,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 80,
|
"execution_count": null,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1261,7 +1261,7 @@
|
|||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"best_model = str(reg_metrics.sort_values(by=\"RMSE_test\").iloc[0].name)\n",
|
"best_model = str(reg_metrics.sort_values(by=\"RMSE_test\").iloc[0].name) # type: ignore\n",
|
||||||
"\n",
|
"\n",
|
||||||
"display(best_model)"
|
"display(best_model)"
|
||||||
]
|
]
|
||||||
@ -1275,7 +1275,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 81,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1397,7 +1397,7 @@
|
|||||||
"2028 0.0 0.0 13143.86485 13575.291528 "
|
"2028 0.0 0.0 13143.86485 13575.291528 "
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 81,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
@ -1426,7 +1426,7 @@
|
|||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 82,
|
"execution_count": 13,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
@ -1548,7 +1548,7 @@
|
|||||||
"2090 0.0 0.0 8930.93455 11318.629065 "
|
"2090 0.0 0.0 8930.93455 11318.629065 "
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 82,
|
"execution_count": 13,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
|
|||||||
1471
lec5.ipynb
Normal file
1471
lec5.ipynb
Normal file
File diff suppressed because one or more lines are too long
BIN
requirements.txt
Normal file
BIN
requirements.txt
Normal file
Binary file not shown.
27
transformers.py
Normal file
27
transformers.py
Normal file
@ -0,0 +1,27 @@
|
|||||||
|
import numpy as np
|
||||||
|
import pandas as pd
|
||||||
|
from sklearn.base import BaseEstimator, TransformerMixin
|
||||||
|
|
||||||
|
|
||||||
|
class TitanicFeatures(BaseEstimator, TransformerMixin):
|
||||||
|
def __init__(self):
|
||||||
|
pass
|
||||||
|
|
||||||
|
def fit(self, X, y=None):
|
||||||
|
return self
|
||||||
|
|
||||||
|
def transform(self, X, y=None):
|
||||||
|
def get_title(name) -> str:
|
||||||
|
return name.split(",")[1].split(".")[0].strip()
|
||||||
|
|
||||||
|
def get_cabin_type(cabin) -> str:
|
||||||
|
if pd.isna(cabin):
|
||||||
|
return "unknown"
|
||||||
|
return cabin[0]
|
||||||
|
|
||||||
|
X["Is_married"] = [1 if get_title(name) == "Mrs" else 0 for name in X["Name"]]
|
||||||
|
X["Cabin_type"] = [get_cabin_type(cabin) for cabin in X["Cabin"]]
|
||||||
|
return X
|
||||||
|
|
||||||
|
def get_feature_names_out(self, features_in):
|
||||||
|
return np.append(features_in, ["Is_married", "Cabin_type"], axis=0)
|
||||||
100
utils_clusters.py
Normal file
100
utils_clusters.py
Normal file
@ -0,0 +1,100 @@
|
|||||||
|
import math
|
||||||
|
from typing import Dict, List, Tuple
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
from pandas import DataFrame
|
||||||
|
from sklearn import cluster
|
||||||
|
from sklearn.metrics import silhouette_samples, silhouette_score
|
||||||
|
|
||||||
|
|
||||||
|
def run_agglomerative(
|
||||||
|
df: DataFrame, num_clusters: int | None = 2
|
||||||
|
) -> cluster.AgglomerativeClustering:
|
||||||
|
agglomerative = cluster.AgglomerativeClustering(
|
||||||
|
n_clusters=num_clusters,
|
||||||
|
compute_distances=True,
|
||||||
|
)
|
||||||
|
return agglomerative.fit(df)
|
||||||
|
|
||||||
|
|
||||||
|
def get_linkage_matrix(model: cluster.AgglomerativeClustering) -> np.ndarray:
|
||||||
|
counts = np.zeros(model.children_.shape[0]) # type: ignore
|
||||||
|
n_samples = len(model.labels_)
|
||||||
|
for i, merge in enumerate(model.children_): # type: ignore
|
||||||
|
current_count = 0
|
||||||
|
for child_idx in merge:
|
||||||
|
if child_idx < n_samples:
|
||||||
|
current_count += 1
|
||||||
|
else:
|
||||||
|
current_count += counts[child_idx - n_samples]
|
||||||
|
counts[i] = current_count
|
||||||
|
|
||||||
|
return np.column_stack([model.children_, model.distances_, counts]).astype(float)
|
||||||
|
|
||||||
|
|
||||||
|
def print_cluster_result(
|
||||||
|
df: DataFrame, clusters_num: int, labels: np.ndarray, separator: str = ", "
|
||||||
|
):
|
||||||
|
for cluster_id in range(clusters_num):
|
||||||
|
cluster_indices = np.where(labels == cluster_id)[0]
|
||||||
|
print(f"Cluster {cluster_id + 1} ({len(cluster_indices)}):")
|
||||||
|
rules = [str(df.index[idx]) for idx in cluster_indices]
|
||||||
|
print(separator.join(rules))
|
||||||
|
print("")
|
||||||
|
print("--------")
|
||||||
|
|
||||||
|
|
||||||
|
def run_kmeans(
|
||||||
|
df: DataFrame, num_clusters: int, random_state: int
|
||||||
|
) -> Tuple[np.ndarray, np.ndarray]:
|
||||||
|
kmeans = cluster.KMeans(n_clusters=num_clusters, random_state=random_state)
|
||||||
|
labels = kmeans.fit_predict(df)
|
||||||
|
return labels, kmeans.cluster_centers_
|
||||||
|
|
||||||
|
|
||||||
|
def fit_kmeans(
|
||||||
|
reduced_data: np.ndarray, num_clusters: int, random_state: int
|
||||||
|
) -> cluster.KMeans:
|
||||||
|
kmeans = cluster.KMeans(n_clusters=num_clusters, random_state=random_state)
|
||||||
|
kmeans.fit(reduced_data)
|
||||||
|
return kmeans
|
||||||
|
|
||||||
|
|
||||||
|
def _get_kmeans_range(
|
||||||
|
df: DataFrame | np.ndarray, random_state: int
|
||||||
|
) -> Tuple[List, range]:
|
||||||
|
max_clusters = int(math.sqrt(len(df)))
|
||||||
|
clusters_range = range(2, max_clusters + 1)
|
||||||
|
kmeans_per_k = [
|
||||||
|
cluster.KMeans(n_clusters=k, random_state=random_state).fit(df)
|
||||||
|
for k in clusters_range
|
||||||
|
]
|
||||||
|
return kmeans_per_k, clusters_range
|
||||||
|
|
||||||
|
|
||||||
|
def get_clusters_inertia(df: DataFrame, random_state: int) -> Tuple[List, range]:
|
||||||
|
kmeans_per_k, clusters_range = _get_kmeans_range(df, random_state)
|
||||||
|
return [model.inertia_ for model in kmeans_per_k], clusters_range
|
||||||
|
|
||||||
|
|
||||||
|
def get_clusters_silhouette_scores(
|
||||||
|
df: DataFrame, random_state: int
|
||||||
|
) -> Tuple[List, range]:
|
||||||
|
kmeans_per_k, clusters_range = _get_kmeans_range(df, random_state)
|
||||||
|
return [
|
||||||
|
float(silhouette_score(df, model.labels_)) for model in kmeans_per_k
|
||||||
|
], clusters_range
|
||||||
|
|
||||||
|
|
||||||
|
def get_clusters_silhouettes(df: np.ndarray, random_state: int) -> Dict:
|
||||||
|
kmeans_per_k, _ = _get_kmeans_range(df, random_state)
|
||||||
|
clusters_silhouettes: Dict = {}
|
||||||
|
for model in kmeans_per_k:
|
||||||
|
silhouette_value = silhouette_score(df, model.labels_)
|
||||||
|
sample_silhouette_values = silhouette_samples(df, model.labels_)
|
||||||
|
clusters_silhouettes[model.n_clusters] = (
|
||||||
|
silhouette_value,
|
||||||
|
sample_silhouette_values,
|
||||||
|
model,
|
||||||
|
)
|
||||||
|
return clusters_silhouettes
|
||||||
242
visual.py
Normal file
242
visual.py
Normal file
@ -0,0 +1,242 @@
|
|||||||
|
from typing import Any, Dict, List
|
||||||
|
|
||||||
|
import matplotlib.cm as cm
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
import numpy as np
|
||||||
|
from pandas import DataFrame
|
||||||
|
from scipy.cluster import hierarchy
|
||||||
|
from sklearn.cluster import KMeans
|
||||||
|
|
||||||
|
|
||||||
|
def draw_data_2d(
|
||||||
|
df: DataFrame,
|
||||||
|
col1: int,
|
||||||
|
col2: int,
|
||||||
|
y: List | None = None,
|
||||||
|
classes: List | None = None,
|
||||||
|
subplot: Any | None = None,
|
||||||
|
):
|
||||||
|
ax = None
|
||||||
|
if subplot is None:
|
||||||
|
_, ax = plt.subplots()
|
||||||
|
else:
|
||||||
|
ax = subplot
|
||||||
|
scatter = ax.scatter(df[df.columns[col1]], df[df.columns[col2]], c=y)
|
||||||
|
ax.set(xlabel=df.columns[col1], ylabel=df.columns[col2])
|
||||||
|
if classes is not None:
|
||||||
|
ax.legend(
|
||||||
|
scatter.legend_elements()[0], classes, loc="lower right", title="Classes"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def draw_dendrogram(linkage_matrix: np.ndarray):
|
||||||
|
hierarchy.dendrogram(linkage_matrix, truncate_mode="level", p=3)
|
||||||
|
|
||||||
|
|
||||||
|
def draw_cluster_results(
|
||||||
|
df: DataFrame,
|
||||||
|
col1: int,
|
||||||
|
col2: int,
|
||||||
|
labels: np.ndarray,
|
||||||
|
cluster_centers: np.ndarray,
|
||||||
|
subplot: Any | None = None,
|
||||||
|
):
|
||||||
|
ax = None
|
||||||
|
if subplot is None:
|
||||||
|
ax = plt
|
||||||
|
else:
|
||||||
|
ax = subplot
|
||||||
|
|
||||||
|
centroids = cluster_centers
|
||||||
|
u_labels = np.unique(labels)
|
||||||
|
|
||||||
|
for i in u_labels:
|
||||||
|
ax.scatter(
|
||||||
|
df[labels == i][df.columns[col1]],
|
||||||
|
df[labels == i][df.columns[col2]],
|
||||||
|
label=i,
|
||||||
|
)
|
||||||
|
|
||||||
|
ax.scatter(centroids[:, col1], centroids[:, col2], s=80, color="k")
|
||||||
|
|
||||||
|
|
||||||
|
def draw_clusters(reduced_data: np.ndarray, kmeans: KMeans):
|
||||||
|
h = 0.02
|
||||||
|
|
||||||
|
x_min, x_max = reduced_data[:, 0].min() - 1, reduced_data[:, 0].max() + 1
|
||||||
|
y_min, y_max = reduced_data[:, 1].min() - 1, reduced_data[:, 1].max() + 1
|
||||||
|
xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
|
||||||
|
|
||||||
|
Z = kmeans.predict(np.c_[xx.ravel(), yy.ravel()])
|
||||||
|
|
||||||
|
Z = Z.reshape(xx.shape)
|
||||||
|
plt.figure(1)
|
||||||
|
plt.clf()
|
||||||
|
plt.imshow(
|
||||||
|
Z,
|
||||||
|
interpolation="nearest",
|
||||||
|
extent=(xx.min(), xx.max(), yy.min(), yy.max()),
|
||||||
|
cmap=plt.cm.Paired, # type: ignore
|
||||||
|
aspect="auto",
|
||||||
|
origin="lower",
|
||||||
|
)
|
||||||
|
|
||||||
|
plt.plot(reduced_data[:, 0], reduced_data[:, 1], "k.", markersize=2)
|
||||||
|
centroids = kmeans.cluster_centers_
|
||||||
|
plt.scatter(
|
||||||
|
centroids[:, 0],
|
||||||
|
centroids[:, 1],
|
||||||
|
marker="x",
|
||||||
|
s=169,
|
||||||
|
linewidths=3,
|
||||||
|
color="w",
|
||||||
|
zorder=10,
|
||||||
|
)
|
||||||
|
plt.title(
|
||||||
|
"K-means clustering (PCA-reduced data)\n"
|
||||||
|
"Centroids are marked with white cross"
|
||||||
|
)
|
||||||
|
plt.xlim(x_min, x_max)
|
||||||
|
plt.ylim(y_min, y_max)
|
||||||
|
plt.xticks(())
|
||||||
|
plt.yticks(())
|
||||||
|
|
||||||
|
|
||||||
|
def _draw_cluster_scores(
|
||||||
|
data: List,
|
||||||
|
clusters_range: range,
|
||||||
|
score_name: str,
|
||||||
|
title: str,
|
||||||
|
):
|
||||||
|
plt.figure(figsize=(8, 5))
|
||||||
|
plt.plot(clusters_range, data, "bo-")
|
||||||
|
plt.xlabel("$k$", fontsize=8)
|
||||||
|
plt.ylabel(score_name, fontsize=8)
|
||||||
|
plt.title(title)
|
||||||
|
|
||||||
|
|
||||||
|
def draw_elbow_diagram(inertias: List, clusters_range: range):
|
||||||
|
_draw_cluster_scores(inertias, clusters_range, "Inertia", "The Elbow Diagram")
|
||||||
|
|
||||||
|
|
||||||
|
def draw_silhouettes_diagram(silhouette: List, clusters_range: range):
|
||||||
|
_draw_cluster_scores(
|
||||||
|
silhouette, clusters_range, "Silhouette score", "The Silhouette score"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _draw_silhouette(
|
||||||
|
ax: Any,
|
||||||
|
reduced_data: np.ndarray,
|
||||||
|
n_clusters: int,
|
||||||
|
silhouette_avg: float,
|
||||||
|
sample_silhouette_values: List,
|
||||||
|
cluster_labels: List,
|
||||||
|
):
|
||||||
|
ax.set_xlim([-0.1, 1])
|
||||||
|
ax.set_ylim([0, len(reduced_data) + (n_clusters + 1) * 10])
|
||||||
|
|
||||||
|
y_lower = 10
|
||||||
|
for i in range(n_clusters):
|
||||||
|
ith_cluster_silhouette_values = sample_silhouette_values[cluster_labels == i]
|
||||||
|
|
||||||
|
ith_cluster_silhouette_values.sort()
|
||||||
|
|
||||||
|
size_cluster_i = ith_cluster_silhouette_values.shape[0]
|
||||||
|
y_upper = y_lower + size_cluster_i
|
||||||
|
|
||||||
|
color = cm.nipy_spectral(float(i) / n_clusters) # type: ignore
|
||||||
|
ax.fill_betweenx(
|
||||||
|
np.arange(y_lower, y_upper),
|
||||||
|
0,
|
||||||
|
ith_cluster_silhouette_values,
|
||||||
|
facecolor=color,
|
||||||
|
edgecolor=color,
|
||||||
|
alpha=0.7,
|
||||||
|
)
|
||||||
|
|
||||||
|
ax.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i))
|
||||||
|
|
||||||
|
y_lower = y_upper + 10 # 10 for the 0 samples
|
||||||
|
|
||||||
|
ax.set_title("The silhouette plot for the various clusters.")
|
||||||
|
ax.set_xlabel("The silhouette coefficient values")
|
||||||
|
ax.set_ylabel("Cluster label")
|
||||||
|
|
||||||
|
ax.axvline(x=silhouette_avg, color="red", linestyle="--")
|
||||||
|
|
||||||
|
ax.set_yticks([])
|
||||||
|
ax.set_xticks([-0.1, 0, 0.2, 0.4, 0.6, 0.8, 1])
|
||||||
|
|
||||||
|
|
||||||
|
def _draw_cluster_data(
|
||||||
|
ax: Any,
|
||||||
|
reduced_data: np.ndarray,
|
||||||
|
n_clusters: int,
|
||||||
|
cluster_labels: np.ndarray,
|
||||||
|
cluster_centers: np.ndarray,
|
||||||
|
):
|
||||||
|
colors = cm.nipy_spectral(cluster_labels.astype(float) / n_clusters) # type: ignore
|
||||||
|
ax.scatter(
|
||||||
|
reduced_data[:, 0],
|
||||||
|
reduced_data[:, 1],
|
||||||
|
marker=".",
|
||||||
|
s=30,
|
||||||
|
lw=0,
|
||||||
|
alpha=0.7,
|
||||||
|
c=colors,
|
||||||
|
edgecolor="k",
|
||||||
|
)
|
||||||
|
|
||||||
|
ax.scatter(
|
||||||
|
cluster_centers[:, 0],
|
||||||
|
cluster_centers[:, 1],
|
||||||
|
marker="o",
|
||||||
|
c="white",
|
||||||
|
alpha=1,
|
||||||
|
s=200,
|
||||||
|
edgecolor="k",
|
||||||
|
)
|
||||||
|
|
||||||
|
for i, c in enumerate(cluster_centers):
|
||||||
|
ax.scatter(c[0], c[1], marker="$%d$" % i, alpha=1, s=50, edgecolor="k")
|
||||||
|
|
||||||
|
ax.set_title("The visualization of the clustered data.")
|
||||||
|
ax.set_xlabel("Feature space for the 1st feature")
|
||||||
|
ax.set_ylabel("Feature space for the 2nd feature")
|
||||||
|
|
||||||
|
|
||||||
|
def draw_silhouettes(reduced_data: np.ndarray, silhouettes: Dict):
|
||||||
|
for key, value in silhouettes.items():
|
||||||
|
fig, (ax1, ax2) = plt.subplots(1, 2)
|
||||||
|
fig.set_size_inches(18, 7)
|
||||||
|
|
||||||
|
n_clusters = key
|
||||||
|
silhouette_avg = value[0]
|
||||||
|
sample_silhouette_values = value[1]
|
||||||
|
cluster_labels = value[2].labels_
|
||||||
|
cluster_centers = value[2].cluster_centers_
|
||||||
|
|
||||||
|
_draw_silhouette(
|
||||||
|
ax1,
|
||||||
|
reduced_data,
|
||||||
|
n_clusters,
|
||||||
|
silhouette_avg,
|
||||||
|
sample_silhouette_values,
|
||||||
|
cluster_labels,
|
||||||
|
)
|
||||||
|
|
||||||
|
_draw_cluster_data(
|
||||||
|
ax2,
|
||||||
|
reduced_data,
|
||||||
|
n_clusters,
|
||||||
|
cluster_labels,
|
||||||
|
cluster_centers,
|
||||||
|
)
|
||||||
|
|
||||||
|
plt.suptitle(
|
||||||
|
"Silhouette analysis for KMeans clustering on sample data with n_clusters = %d"
|
||||||
|
% n_clusters,
|
||||||
|
fontsize=14,
|
||||||
|
fontweight="bold",
|
||||||
|
)
|
||||||
Loading…
Reference in New Issue
Block a user