From f0ff63972213daba950d3e7b2d961ff7190011a2 Mon Sep 17 00:00:00 2001 From: ujijrujijr Date: Sun, 16 Feb 2025 16:41:38 +0400 Subject: [PATCH 1/5] =?UTF-8?q?=D0=9F=D0=BE=D0=BF=D1=80=D0=B0=D0=B2=D0=B8?= =?UTF-8?q?=D1=82=D1=8C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_7/Lab7.ipynb | 876 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 876 insertions(+) create mode 100644 lab_7/Lab7.ipynb diff --git a/lab_7/Lab7.ipynb b/lab_7/Lab7.ipynb new file mode 100644 index 0000000..3b3a163 --- /dev/null +++ b/lab_7/Lab7.ipynb @@ -0,0 +1,876 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "games.csv - датасет игр из steam" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"..//static//csv//games.csv\")\n", + "\n", + "# df['date_release'] = pd.to_datetime(df['date_release'])\n", + "# # Разделение даты на год, месяц и день\n", + "# df['year'] = df['date_release'].dt.year\n", + "# df['month'] = df['date_release'].dt.month\n", + "# df['day'] = df['date_release'].dt.day\n", + "\n", + "# # Удаляем исходный столбец 'date', если он больше не нужен\n", + "# df.drop('date', axis=1, inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Входные переменные: user_reviews (кол-во отзывов игроков; reviews в коде), price_original (цена на момент выхода; price в коде)\n", + "\n", + "Выходная перменная: positive_ratio (отношение положительных отзывов к негативным; pos в коде)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime as dt\n", + "from datetime import timedelta\n", + "\n", + "import matplotlib.pyplot as plt\n", + "from skfuzzy import control as ctrl\n", + "import skfuzzy as fuzz\n", + "\n", + "#входная переменная кол-ва отзывов с таким универсумом (от 0 до 100k)\n", + "reviews = ctrl.Antecedent(np.arange(0, 100000, 1), \"reviews\")\n", + "\n", + "#входная переменная цены с таким универсумом (от 0 до 100 долларов)\n", + "price = ctrl.Antecedent(np.arange(0, 100, 0.01), \"price\")\n", + "\n", + "#удалить пару игр, у которых цена больше 100 долларов, чтобы графики норм. были\n", + "df = df[df['price_original'] <= 100]\n", + "\n", + "#удалить несколько игр, у которых больше 100k отзывов, чтобы графики норм. были\n", + "df = df[df['user_reviews'] <= 100000]\n", + "\n", + "#выходная переменная позитивности с таким универсумом (от 0 до 100)\n", + "pos = ctrl.Consequent(np.arange(0, 100, 1), \"pos\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Лингвистические переменные и их визуализация" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\AI labs\\aimenv\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n", + " fig.show()\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#ЛИНГВИСТИЧЕСКАЯ ПЕР. КОЛ-ВО ОТЗЫВОВ\n", + "\n", + "#определял примерные диапазоны для кол-ва отзывов с помощью boxplot:\n", + "# plt.figure(figsize=(12, 8))\n", + "# df_temp = df[df['user_reviews'] < 100000] \n", + "# plt.boxplot(x=df_temp['user_reviews'])\n", + "# plt.show()\n", + "\n", + "#автоматическое формирование нечёт. переменной отзывов, но с поправкой для many (s - ф-ия) \n", + "reviews.automf(3, variable_type=\"quant\", names=['few', 'avg', 'many'])\n", + "reviews[\"few\"] = fuzz.zmf(reviews.universe, 0, 10000)\n", + "\n", + "reviews[\"many\"] = fuzz.smf(reviews.universe, reviews.universe.max()/2, reviews.universe.max())\n", + "reviews.view()\n", + "\n", + "#СТАРЫЙ КОД\n", + "#---------------------------------------------------------------------------\n", + "# #до 15 обзоров - мало\n", + "# #z-функция\n", + "# reviews[\"few\"] = fuzz.zmf(reviews.universe, 0, 15)\n", + "\n", + "# #10-40 обзоров - средне\n", + "# #треуг. ф-ия\n", + "# # 10 - левая вершина треугольника\n", + "# # 25 - верхняя вершина\n", + "# # 40 - правая вершина\n", + "# reviews[\"average\"] = fuzz.trimf(reviews.universe, [10, 25, 40]) \n", + "\n", + "# #больше 30 обзоров - много\n", + "# #s-функция\n", + "# reviews[\"many\"] = fuzz.smf(reviews.universe, 30, reviews.universe.max())\n", + "\n", + "# reviews.view()\n", + "\n", + "#---------------------------------------------------------------------------\n", + "\n", + "\n", + "\n", + "#ЛИНГВИСТИЧЕСКАЯ ПЕР. ЦЕНА\n", + "\n", + "#определял примерные диапазоны для цены с помощью boxplot:\n", + "# plt.figure(figsize=(12, 8))\n", + "# df_temp = df[df['price_original'] < 60]\n", + "# plt.boxplot(x=df_temp['price_original'])\n", + "# plt.show()\n", + "\n", + "#От 0 до 10 долларов можно считать дёшево (переводил на рубли)\n", + "#z-функция\n", + "# price[\"cheap\"] = fuzz.zmf(price.universe, 0, 10)\n", + "price[\"cheap\"] = fuzz.zmf(price.universe, 0, 12)\n", + "\n", + "#от 5 до 22 долларов можно считать средне (переводил на рубли)\n", + "#треуг. ф-ия\n", + "# 5 - левая вершина треугольника\n", + "# 15 - верхняя вершина\n", + "# 22 - правая вершина\n", + "# price[\"medium\"] = fuzz.trimf(price.universe, [5, 15, 22])\n", + "price[\"medium\"] = fuzz.trimf(price.universe, [5, 16, 22])\n", + "\n", + "#больше 15 долларов можно считать дорого (переводил на рубли)\n", + "#s-функция\n", + "price[\"expensive\"] = fuzz.smf(price.universe, 15, price.universe.max())\n", + "\n", + "price.view()\n", + "\n", + "\n", + "#ЛИНГВИСТИЧЕСКАЯ ПЕР. СООТНОШЕНИЕ ПОЛОЖ./НЕГАТИВ. ОТЗЫВОВ\n", + "#до 60% можно считать низким отношением позитивных к негативным\n", + "\n", + "# pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", + "\n", + "# #от 50 до 80 можно считать средним\n", + "# pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", + "\n", + "# #от 75 можно считать высоким\n", + "# pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", + "\n", + "\n", + "\n", + "pos.view()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## База нечётких правил" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " user_reviews price_original positive_ratio\n", + "15251 46 0.99 95\n", + "13770 491 6.99 83\n", + "21390 365 0.00 76\n", + "16365 55 2.99 96\n", + "49100 78 0.00 74\n", + "... ... ... ...\n", + "2652 55 14.99 74\n", + "30351 41 9.99 82\n", + "1810 4598 59.99 92\n", + "27959 115 2.99 73\n", + "2864 15 4.99 86\n", + "\n", + "[10142 rows x 3 columns]\n" + ] + }, + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "user_reviews", + "rawType": "int64", + "type": "integer" + }, + { + "name": "price_original", + "rawType": "float64", + "type": "float" + }, + { + "name": "positive_ratio", + "rawType": "int64", + "type": "integer" + }, + { + "name": "positive_ratio_pred", + "rawType": "float64", + "type": "float" + } + ], + "conversionMethod": "pd.DataFrame", + "ref": "b6864b03-4b3a-442d-9c1f-6251995181a1", + "rows": [ + [ + "15251", + "46", + "0.99", + "95", + "92.04448967992606" + ], + [ + "13770", + "491", + "6.99", + "83", + "74.78591007701688" + ], + [ + "21390", + "365", + "0.0", + "76", + "91.64031295698327" + ], + [ + "16365", + "55", + "2.99", + "96", + "91.73922119826041" + ], + [ + "49100", + "78", + "0.0", + "74", + "92.01041272015634" + ], + [ + "4586", + "310", + "9.99", + "64", + 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" + ], + "text/plain": [ + " user_reviews price_original positive_ratio positive_ratio_pred\n", + "15251 46 0.99 95 92.044490\n", + "13770 491 6.99 83 74.785910\n", + "21390 365 0.00 76 91.640313\n", + "16365 55 2.99 96 91.739221\n", + "49100 78 0.00 74 92.010413\n", + "... ... ... ... ...\n", + "2652 55 14.99 74 66.698909\n", + "30351 41 9.99 82 66.142143\n", + "1810 4598 59.99 92 24.863128\n", + "27959 115 2.99 73 91.657627\n", + "2864 15 4.99 86 90.861111\n", + "\n", + "[10142 rows x 4 columns]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rule1 = ctrl.Rule(reviews['many'] & price['cheap'], pos['high'])\n", + "rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", + "rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", + "\n", + "rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) #avg\n", + "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['avg']) #avg\n", + "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['low'])\n", + "\n", + "rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['avg'])\n", + "rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", + "rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['avg'])\n", + "\n", + "\n", + "\n", + "#ЗДЕСЬ ДОПОЛНИТЬ, ЕСЛИ БУДЕТ ДОП. ПРАВИЛО:\n", + "fuzzy_rules = [\n", + " rule1,\n", + " rule2,\n", + " rule3,\n", + " rule4,\n", + " rule5,\n", + " rule6,\n", + " rule7,\n", + " rule8,\n", + " rule9\n", + "]\n", + "\n", + "fuzzy_sys = ctrl.ControlSystemSimulation(ctrl.ControlSystem(fuzzy_rules))\n", + "\n", + "#ТУТ ПОМЕНЯТЬ НАЗВАНИЯ СТОЛБЦОВ И НЕЧЁТКИХ ПЕРЕМЕННЫХ НА СВОИ\n", + "def fuzzy_pred(row):\n", + " # al - нечёт. пер. ; al2o3 - столбец датасета\n", + " fuzzy_sys.input[\"reviews\"] = row[\"user_reviews\"]\n", + " fuzzy_sys.input[\"price\"] = row[\"price_original\"]\n", + " fuzzy_sys.compute()\n", + " # return fuzzy_sys.output[\"positive_ratio\"]\n", + " return fuzzy_sys.output[\"pos\"]\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "#РАЗДЕЛИТЬ ДАТАСЕТ НА ОБУЧАЮЩУЮ, ТЕСТОВУЮ ВЫБОРКИ\n", + "#Тестирование нечеткой системы на тестовой выборке\n", + "# Разделение данных на обучающую и тестовую выборки\n", + "X = df[['user_reviews', 'price_original']]\n", + "y = df['positive_ratio']\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n", + "\n", + "test = pd.concat([X_test, y_test], axis=1)\n", + "\n", + "\n", + "print(test)\n", + "\n", + "result_test = test.copy()\n", + "result_test[\"positive_ratio_pred\"] = result_test.apply(fuzzy_pred, axis=1)\n", + "result_test" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R^2 = -0.9549582516266943\n", + "RMSE = 25.637064888955464\n" + ] + } + ], + "source": [ + "#Оценка\n", + "import math\n", + "from sklearn import metrics\n", + "print(f\"R^2 = {metrics.r2_score(result_test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])}\")\n", + "print(f\"RMSE = {math.sqrt(\n", + " metrics.mean_squared_error(result_test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])\n", + ")}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Оценки показали, что нечёткая система очень плохо справляется с предсказанием соотношения положительных отзывов к негативным. \n", + "\n", + "Средняя квадратичная ошибка составляет почти 41%, что является большой ошибкой для диапазона от 0 до 100. \n", + "\n", + "Коэффициент детерминации получился отрицательным. Это означает, что система работает хуже, чем простое предсказание средним значением. Это говорит о том, что гипотезы о зависимости положительности отзывов от цены игры и количества отзывов, проявляемые в виде базы нечётких правил, неправильно отражают действительность. Возможно, что распределение отношений положительных отзывов к отрицательным имеет скорее случайный характер, поэтому оно не может быть описано с хорошей точностью нечёткими правилами" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "aimenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 62c53c7352f93830924142340fd3e17a2b79e7bb Mon Sep 17 00:00:00 2001 From: ujijrujijr Date: Sun, 16 Feb 2025 16:42:54 +0400 Subject: [PATCH 2/5] =?UTF-8?q?=D0=9F=D0=B5=D1=80=D0=B5=D0=B4=20=D0=BF?= =?UTF-8?q?=D1=80=D0=BE=D0=B1=D0=BE=D0=B9=20=D0=BF=D0=B5=D1=80=D0=B5=D0=B4?= =?UTF-8?q?=D0=B5=D0=BB=D0=B0=D1=82=D1=8C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_7/Lab7.ipynb | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/lab_7/Lab7.ipynb b/lab_7/Lab7.ipynb index 3b3a163..feb62e1 100644 --- a/lab_7/Lab7.ipynb +++ b/lab_7/Lab7.ipynb @@ -195,13 +195,13 @@ "#ЛИНГВИСТИЧЕСКАЯ ПЕР. СООТНОШЕНИЕ ПОЛОЖ./НЕГАТИВ. ОТЗЫВОВ\n", "#до 60% можно считать низким отношением позитивных к негативным\n", "\n", - "# pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", + "pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", "\n", - "# #от 50 до 80 можно считать средним\n", - "# pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", + "#от 50 до 80 можно считать средним\n", + "pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", "\n", - "# #от 75 можно считать высоким\n", - "# pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", + "#от 75 можно считать высоким\n", + "pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", "\n", "\n", "\n", @@ -217,7 +217,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -271,7 +271,7 @@ } ], "conversionMethod": "pd.DataFrame", - "ref": "b6864b03-4b3a-442d-9c1f-6251995181a1", + "ref": "ef5067fd-ef97-48d3-a20a-5506a12af29b", "rows": [ [ "15251", @@ -754,7 +754,7 @@ "[10142 rows x 4 columns]" ] }, - "execution_count": 31, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -818,7 +818,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 34, "metadata": {}, "outputs": [ { From 3507e1d14290ebe75497c3824c14187433eac5ae Mon Sep 17 00:00:00 2001 From: ujijrujijr Date: Sun, 16 Feb 2025 16:51:10 +0400 Subject: [PATCH 3/5] =?UTF-8?q?=D0=BF=D0=BE=D0=BB=D1=83=D1=87=D1=88=D0=B5?= =?UTF-8?q?=20=D0=BE=D1=86=D0=B5=D0=BD=D0=BA=D0=B8?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_7/Lab7.ipynb | 204 +++++++++++++++++++++++++---------------------- 1 file changed, 109 insertions(+), 95 deletions(-) diff --git a/lab_7/Lab7.ipynb b/lab_7/Lab7.ipynb index feb62e1..36a7f5a 100644 --- a/lab_7/Lab7.ipynb +++ b/lab_7/Lab7.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -83,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -106,7 +106,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -195,14 +195,15 @@ "#ЛИНГВИСТИЧЕСКАЯ ПЕР. СООТНОШЕНИЕ ПОЛОЖ./НЕГАТИВ. ОТЗЫВОВ\n", "#до 60% можно считать низким отношением позитивных к негативным\n", "\n", - "pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", + "# pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", "\n", - "#от 50 до 80 можно считать средним\n", - "pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", + "# #от 50 до 80 можно считать средним\n", + "# pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", "\n", - "#от 75 можно считать высоким\n", - "pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", + "# #от 75 можно считать высоким\n", + "# pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", "\n", + "pos.automf(5, variable_type=\"quant\")\n", "\n", "\n", "pos.view()" @@ -217,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -271,357 +272,357 @@ } ], "conversionMethod": "pd.DataFrame", - "ref": "ef5067fd-ef97-48d3-a20a-5506a12af29b", + "ref": "5922a94b-2599-4b50-a82a-b7ba0c907a61", "rows": [ [ "15251", "46", "0.99", "95", - "92.04448967992606" + "74.20947677900149" ], [ "13770", "491", "6.99", "83", - "74.78591007701688" + "74.2664254885942" ], [ "21390", "365", "0.0", "76", - "91.64031295698327" + "73.97023837640037" ], [ "16365", "55", "2.99", "96", - "91.73922119826041" + "74.20189499201257" ], [ "49100", "78", "0.0", "74", - "92.01041272015634" + "74.18496967806658" ], [ "4586", "310", "9.99", "64", - "66.3556049919213" + "84.72672777048702" ], [ "44242", "45", "4.99", "55", - "90.80660919873473" + "74.20491838793168" ], [ "34788", "24", "4.99", "54", - "90.84473436906006" + "74.2232467570519" ], [ "8555", "450", "17.99", "92", - "66.15407457648809" + "88.79909989039582" ], [ "14595", "121", "7.99", "96", - "69.7335265397698" + "76.49966400675864" ], [ "45078", "560", "0.0", "91", - "91.39376995217687" + "73.82931758417166" ], [ "34398", "16", "9.99", "68", - "66.1221026320288" + "85.42844449685683" ], [ "46955", "10", "0.0", "80", - "92.0985091592291" + "74.23717681900094" ], [ "38856", "1641", "0.0", "22", - 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"63.91979082569322" + "85.46326054861929" ], [ "16976", "548", "1.99", "80", - "91.31237690194502" + "73.83684137272655" ], [ "26878", "17", "0.99", "100", - "92.08214560105175" + "74.23178244254356" ], [ "14773", "1232", "0.0", "77", - "90.55162620039864" + "73.35468135027476" ], [ "49833", "22", "14.99", "100", - "66.67957254094878" + "90.6548717946924" ], [ "38505", "122", "9.99", "67", - "66.20683766026289" + "85.17071414705808" ], [ "43580", "873", "0.0", "86", - "90.99968195314106" + "73.60777194587104" ], [ "4218", "1648", "3.99", "97", - "89.13792450265012" + "73.00862449061341" ], [ "26855", "16", "0.99", "93", - "92.08344624744724" + "74.23255328168158" ], [ "45102", "10", "0.0", "90", - "92.0985091592291" + "74.23717681900094" ], [ "11517", "19", "14.99", "84", - "66.67781306410103" + "90.65846762335833" ], [ "35603", "11", "3.99", "54", - "91.43288531170177" + "74.23576480487064" ], [ "32164", "16", "7.99", "56", - "69.7335265397698" + "76.68576266295884" ], [ "9740", "123", "9.99", "82", - "66.20763409075975" + "85.16830848356211" ], [ "50391", "24", "0.0", "83", - "92.08031725509622" + "74.22638605426216" ], [ "16492", "696", "19.99", "86", - "64.71772943509656" + "84.47340305190548" ], [ "37115", "31", "1.99", "54", - "91.98287898755996" + "74.22097099873041" ], [ "9948", "68", "2.99", "91", - "91.72149391995458" + "74.1917872528175" ], [ "35890", "837", "0.99", "69", - "91.04059922851958" + "73.63302720049518" ], [ "45995", "19", "0.0", "57", - "92.08681111572254" + "74.23023737869836" ], [ "19896", "1084", "19.99", "84", - "65.17326840440721" + "83.92495287088245" ], [ "12818", "10", "1.99", "100", - "92.01051210610092" + "74.23719300952487" ], [ "2729", "744", "7.99", "88", - "69.7335265397698" + "75.46558507027298" ], [ "38237", "59", "0.0", "91", - "92.03496102642863" + "74.19950502946304" ] ], "shape": { @@ -660,35 +661,35 @@ " 46\n", " 0.99\n", " 95\n", - " 92.044490\n", + " 74.209477\n", " \n", " \n", " 13770\n", " 491\n", " 6.99\n", " 83\n", - " 74.785910\n", + " 74.266425\n", " \n", " \n", " 21390\n", " 365\n", " 0.00\n", " 76\n", - " 91.640313\n", + " 73.970238\n", " \n", " \n", " 16365\n", " 55\n", " 2.99\n", " 96\n", - " 91.739221\n", + " 74.201895\n", " \n", " \n", " 49100\n", " 78\n", " 0.00\n", " 74\n", - " 92.010413\n", + " 74.184970\n", " \n", " \n", " ...\n", @@ -702,35 +703,35 @@ " 55\n", " 14.99\n", " 74\n", - " 66.698909\n", + " 90.615416\n", " \n", " \n", " 30351\n", " 41\n", " 9.99\n", " 82\n", - " 66.142143\n", + " 85.367169\n", " \n", " \n", " 1810\n", " 4598\n", " 59.99\n", " 92\n", - " 24.863128\n", + " 28.455605\n", " \n", " \n", " 27959\n", " 115\n", " 2.99\n", " 73\n", - " 91.657627\n", + " 74.155404\n", " \n", " \n", " 2864\n", " 15\n", " 4.99\n", " 86\n", - " 90.861111\n", + " 74.231120\n", " \n", " \n", "\n", @@ -739,40 +740,50 @@ ], "text/plain": [ " user_reviews price_original positive_ratio positive_ratio_pred\n", - "15251 46 0.99 95 92.044490\n", - "13770 491 6.99 83 74.785910\n", - "21390 365 0.00 76 91.640313\n", - "16365 55 2.99 96 91.739221\n", - "49100 78 0.00 74 92.010413\n", + "15251 46 0.99 95 74.209477\n", + "13770 491 6.99 83 74.266425\n", + "21390 365 0.00 76 73.970238\n", + "16365 55 2.99 96 74.201895\n", + "49100 78 0.00 74 74.184970\n", "... ... ... ... ...\n", - "2652 55 14.99 74 66.698909\n", - "30351 41 9.99 82 66.142143\n", - "1810 4598 59.99 92 24.863128\n", - "27959 115 2.99 73 91.657627\n", - "2864 15 4.99 86 90.861111\n", + "2652 55 14.99 74 90.615416\n", + "30351 41 9.99 82 85.367169\n", + "1810 4598 59.99 92 28.455605\n", + "27959 115 2.99 73 74.155404\n", + "2864 15 4.99 86 74.231120\n", "\n", "[10142 rows x 4 columns]" ] }, - "execution_count": 33, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "# rule1 = ctrl.Rule(reviews['many'] & price['cheap'], pos['high'])\n", + "# rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", + "# rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", + "\n", + "# rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) #avg\n", + "# rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['avg']) #avg\n", + "# rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['low'])\n", + "\n", + "# rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['avg'])\n", + "# rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", + "# rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['avg'])\n", + "\n", "rule1 = ctrl.Rule(reviews['many'] & price['cheap'], pos['high'])\n", "rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", "rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", "\n", "rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) #avg\n", - "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['avg']) #avg\n", + "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['higher']) #avg\n", "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['low'])\n", "\n", - "rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['avg'])\n", + "rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['average'])\n", "rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", - "rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['avg'])\n", - "\n", - "\n", + "rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['average'])\n", "\n", "#ЗДЕСЬ ДОПОЛНИТЬ, ЕСЛИ БУДЕТ ДОП. ПРАВИЛО:\n", "fuzzy_rules = [\n", @@ -818,15 +829,15 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "R^2 = -0.9549582516266943\n", - "RMSE = 25.637064888955464\n" + "R^2 = -0.6240120497062605\n", + "RMSE = 23.36652781503876\n" ] } ], @@ -844,11 +855,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Оценки показали, что нечёткая система очень плохо справляется с предсказанием соотношения положительных отзывов к негативным. \n", + "Оценки показали, что построенная нечёткая система плохо справляется с предсказанием соотношения положительных отзывов к негативным. \n", "\n", - "Средняя квадратичная ошибка составляет почти 41%, что является большой ошибкой для диапазона от 0 до 100. \n", + "Средняя квадратичная ошибка составляет почти 25%, что является большой ошибкой для диапазона от 0 до 100. \n", "\n", - "Коэффициент детерминации получился отрицательным. Это означает, что система работает хуже, чем простое предсказание средним значением. Это говорит о том, что гипотезы о зависимости положительности отзывов от цены игры и количества отзывов, проявляемые в виде базы нечётких правил, неправильно отражают действительность. Возможно, что распределение отношений положительных отзывов к отрицательным имеет скорее случайный характер, поэтому оно не может быть описано с хорошей точностью нечёткими правилами" + "Коэффициент детерминации получился отрицательным. Это означает, что система работает хуже, чем простое предсказание средним значением. Это говорит о том, что гипотезы о зависимости положительности отзывов от цены игры и количества отзывов, проявляемые в виде базы нечётких правил, неправильно отражают действительность. \n", + "\n", + "\n", + "Возможно, что распределение отношений положительных отзывов к отрицательным имеет скорее случайный характер, поэтому оно не может быть описано с хорошей точностью нечёткими правилами" ] } ], From 4e8aeacb26fb82686c12b73e40a50d12a0905579 Mon Sep 17 00:00:00 2001 From: ujijrujijr Date: Sun, 16 Feb 2025 18:04:40 +0400 Subject: [PATCH 4/5] =?UTF-8?q?=D0=BF=D0=BE=D0=BB=D1=83=D1=87=D1=88=D0=B5?= =?UTF-8?q?=20=D0=BE=D1=86=D0=B5=D0=BD=D0=BA=D0=B8=201?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_7/Lab7.ipynb | 48 +++++++++++++++++++++++------------------------- 1 file changed, 23 insertions(+), 25 deletions(-) diff --git a/lab_7/Lab7.ipynb b/lab_7/Lab7.ipynb index 36a7f5a..bde5b1c 100644 --- a/lab_7/Lab7.ipynb +++ b/lab_7/Lab7.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 70, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 71, "metadata": {}, "outputs": [], "source": [ @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 72, "metadata": {}, "outputs": [], "source": [ @@ -83,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -218,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -272,7 +272,7 @@ } ], "conversionMethod": "pd.DataFrame", - "ref": "5922a94b-2599-4b50-a82a-b7ba0c907a61", + "ref": "6df9d4d6-0a40-404e-b085-39cbd7b0c963", "rows": [ [ "15251", @@ -335,7 +335,7 @@ "450", "17.99", "92", - "88.79909989039582" + "89.20378747679185" ], [ "14595", @@ -447,7 +447,7 @@ "28", "17.99", "96", - "89.30806692369116" + "89.60745365568543" ], [ "11451", @@ -461,7 +461,7 @@ "50", "19.99", "68", - "85.46326054861929" + "86.68910788534616" ], [ "16976", @@ -566,7 +566,7 @@ "696", "19.99", "86", - "84.47340305190548" + "86.10011067019401" ], [ "37115", @@ -601,7 +601,7 @@ "1084", "19.99", "84", - "83.92495287088245" + "85.49351318658027" ], [ "12818", @@ -717,7 +717,7 @@ " 4598\n", " 59.99\n", " 92\n", - " 28.455605\n", + " 49.500000\n", " \n", " \n", " 27959\n", @@ -748,14 +748,14 @@ "... ... ... ... ...\n", "2652 55 14.99 74 90.615416\n", "30351 41 9.99 82 85.367169\n", - "1810 4598 59.99 92 28.455605\n", + "1810 4598 59.99 92 49.500000\n", "27959 115 2.99 73 74.155404\n", "2864 15 4.99 86 74.231120\n", "\n", "[10142 rows x 4 columns]" ] }, - "execution_count": 45, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" } @@ -777,9 +777,9 @@ "rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", "rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", "\n", - "rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) #avg\n", + "rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) \n", "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['higher']) #avg\n", - "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['low'])\n", + "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['average']) #low\n", "\n", "rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['average'])\n", "rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", @@ -800,13 +800,11 @@ "\n", "fuzzy_sys = ctrl.ControlSystemSimulation(ctrl.ControlSystem(fuzzy_rules))\n", "\n", - "#ТУТ ПОМЕНЯТЬ НАЗВАНИЯ СТОЛБЦОВ И НЕЧЁТКИХ ПЕРЕМЕННЫХ НА СВОИ\n", + "\n", "def fuzzy_pred(row):\n", - " # al - нечёт. пер. ; al2o3 - столбец датасета\n", " fuzzy_sys.input[\"reviews\"] = row[\"user_reviews\"]\n", " fuzzy_sys.input[\"price\"] = row[\"price_original\"]\n", " fuzzy_sys.compute()\n", - " # return fuzzy_sys.output[\"positive_ratio\"]\n", " return fuzzy_sys.output[\"pos\"]\n", "\n", "from sklearn.model_selection import train_test_split\n", @@ -829,15 +827,15 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 75, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "R^2 = -0.6240120497062605\n", - "RMSE = 23.36652781503876\n" + "R^2 = -0.29858167190494145\n", + "RMSE = 20.894606342915804\n" ] } ], @@ -845,9 +843,9 @@ "#Оценка\n", "import math\n", "from sklearn import metrics\n", - "print(f\"R^2 = {metrics.r2_score(result_test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])}\")\n", + "print(f\"R^2 = {metrics.r2_score(test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])}\")\n", "print(f\"RMSE = {math.sqrt(\n", - " metrics.mean_squared_error(result_test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])\n", + " metrics.mean_squared_error(test[\"positive_ratio\"], result_test[\"positive_ratio_pred\"])\n", ")}\")" ] }, @@ -857,7 +855,7 @@ "source": [ "Оценки показали, что построенная нечёткая система плохо справляется с предсказанием соотношения положительных отзывов к негативным. \n", "\n", - "Средняя квадратичная ошибка составляет почти 25%, что является большой ошибкой для диапазона от 0 до 100. \n", + "Средняя квадратичная ошибка составляет примерно 20%, что является достаточно большой ошибкой для диапазона от 0 до 100. \n", "\n", "Коэффициент детерминации получился отрицательным. Это означает, что система работает хуже, чем простое предсказание средним значением. Это говорит о том, что гипотезы о зависимости положительности отзывов от цены игры и количества отзывов, проявляемые в виде базы нечётких правил, неправильно отражают действительность. \n", "\n", From b04cd44f5d38e1c426aee309a6f1aabdb05906fa Mon Sep 17 00:00:00 2001 From: ujijrujijr Date: Fri, 21 Feb 2025 23:40:54 +0400 Subject: [PATCH 5/5] =?UTF-8?q?=D0=92=D1=80=D0=BE=D0=B4=D0=B5=20=D0=BF?= =?UTF-8?q?=D0=BE=D0=B4=D0=BF=D1=80=D0=B0=D0=B2=D0=B8=D0=BB?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab_7/Lab7.ipynb | 92 +++++++++--------------------------------------- 1 file changed, 16 insertions(+), 76 deletions(-) diff --git a/lab_7/Lab7.ipynb b/lab_7/Lab7.ipynb index bde5b1c..cdeb528 100644 --- a/lab_7/Lab7.ipynb +++ b/lab_7/Lab7.ipynb @@ -20,20 +20,11 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "df = pd.read_csv(\"..//static//csv//games.csv\")\n", - "\n", - "# df['date_release'] = pd.to_datetime(df['date_release'])\n", - "# # Разделение даты на год, месяц и день\n", - "# df['year'] = df['date_release'].dt.year\n", - "# df['month'] = df['date_release'].dt.month\n", - "# df['day'] = df['date_release'].dt.day\n", - "\n", - "# # Удаляем исходный столбец 'date', если он больше не нужен\n", - "# df.drop('date', axis=1, inplace=True)" + "df = pd.read_csv(\"..//static//csv//games.csv\")" ] }, { @@ -83,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -128,12 +119,6 @@ "source": [ "#ЛИНГВИСТИЧЕСКАЯ ПЕР. КОЛ-ВО ОТЗЫВОВ\n", "\n", - "#определял примерные диапазоны для кол-ва отзывов с помощью boxplot:\n", - "# plt.figure(figsize=(12, 8))\n", - "# df_temp = df[df['user_reviews'] < 100000] \n", - "# plt.boxplot(x=df_temp['user_reviews'])\n", - "# plt.show()\n", - "\n", "#автоматическое формирование нечёт. переменной отзывов, но с поправкой для many (s - ф-ия) \n", "reviews.automf(3, variable_type=\"quant\", names=['few', 'avg', 'many'])\n", "reviews[\"few\"] = fuzz.zmf(reviews.universe, 0, 10000)\n", @@ -141,40 +126,12 @@ "reviews[\"many\"] = fuzz.smf(reviews.universe, reviews.universe.max()/2, reviews.universe.max())\n", "reviews.view()\n", "\n", - "#СТАРЫЙ КОД\n", - "#---------------------------------------------------------------------------\n", - "# #до 15 обзоров - мало\n", - "# #z-функция\n", - "# reviews[\"few\"] = fuzz.zmf(reviews.universe, 0, 15)\n", - "\n", - "# #10-40 обзоров - средне\n", - "# #треуг. ф-ия\n", - "# # 10 - левая вершина треугольника\n", - "# # 25 - верхняя вершина\n", - "# # 40 - правая вершина\n", - "# reviews[\"average\"] = fuzz.trimf(reviews.universe, [10, 25, 40]) \n", - "\n", - "# #больше 30 обзоров - много\n", - "# #s-функция\n", - "# reviews[\"many\"] = fuzz.smf(reviews.universe, 30, reviews.universe.max())\n", - "\n", - "# reviews.view()\n", - "\n", - "#---------------------------------------------------------------------------\n", - "\n", "\n", "\n", "#ЛИНГВИСТИЧЕСКАЯ ПЕР. ЦЕНА\n", "\n", - "#определял примерные диапазоны для цены с помощью boxplot:\n", - "# plt.figure(figsize=(12, 8))\n", - "# df_temp = df[df['price_original'] < 60]\n", - "# plt.boxplot(x=df_temp['price_original'])\n", - "# plt.show()\n", - "\n", - "#От 0 до 10 долларов можно считать дёшево (переводил на рубли)\n", + "#От 0 до 12 долларов можно считать дёшево (переводил на рубли)\n", "#z-функция\n", - "# price[\"cheap\"] = fuzz.zmf(price.universe, 0, 10)\n", "price[\"cheap\"] = fuzz.zmf(price.universe, 0, 12)\n", "\n", "#от 5 до 22 долларов можно считать средне (переводил на рубли)\n", @@ -182,7 +139,6 @@ "# 5 - левая вершина треугольника\n", "# 15 - верхняя вершина\n", "# 22 - правая вершина\n", - "# price[\"medium\"] = fuzz.trimf(price.universe, [5, 15, 22])\n", "price[\"medium\"] = fuzz.trimf(price.universe, [5, 16, 22])\n", "\n", "#больше 15 долларов можно считать дорого (переводил на рубли)\n", @@ -193,16 +149,6 @@ "\n", "\n", "#ЛИНГВИСТИЧЕСКАЯ ПЕР. СООТНОШЕНИЕ ПОЛОЖ./НЕГАТИВ. ОТЗЫВОВ\n", - "#до 60% можно считать низким отношением позитивных к негативным\n", - "\n", - "# pos[\"low\"] = fuzz.zmf(pos.universe, 0, 60)\n", - "\n", - "# #от 50 до 80 можно считать средним\n", - "# pos[\"avg\"] = fuzz.trimf(pos.universe, [50, 70, 80])\n", - "\n", - "# #от 75 можно считать высоким\n", - "# pos[\"high\"] = fuzz.smf(pos.universe, 75, 100)\n", - "\n", "pos.automf(5, variable_type=\"quant\")\n", "\n", "\n", @@ -218,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -761,31 +707,18 @@ } ], "source": [ - "# rule1 = ctrl.Rule(reviews['many'] & price['cheap'], pos['high'])\n", - "# rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", - "# rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", - "\n", - "# rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) #avg\n", - "# rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['avg']) #avg\n", - "# rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['low'])\n", - "\n", - "# rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['avg'])\n", - "# rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", - "# rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['avg'])\n", - "\n", "rule1 = ctrl.Rule(reviews['many'] & price['cheap'], pos['high'])\n", - "rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) #avg\n", + "rule2 = ctrl.Rule(reviews['many'] & price['medium'], pos['high']) \n", "rule3 = ctrl.Rule(reviews['many'] & price['expensive'], pos['high']) \n", "\n", "rule4 = ctrl.Rule(reviews['few'] & price['cheap'], pos['high']) \n", - "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['higher']) #avg\n", - "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['average']) #low\n", + "rule5 = ctrl.Rule(reviews['few'] & price['medium'], pos['higher'])\n", + "rule6 = ctrl.Rule(reviews['few'] & price['expensive'], pos['average'])\n", "\n", "rule7 = ctrl.Rule(reviews['avg'] & price['cheap'], pos['average'])\n", "rule8 = ctrl.Rule(reviews['avg'] & price['medium'], pos['high'])\n", "rule9 = ctrl.Rule(reviews['avg'] & price['expensive'], pos['average'])\n", "\n", - "#ЗДЕСЬ ДОПОЛНИТЬ, ЕСЛИ БУДЕТ ДОП. ПРАВИЛО:\n", "fuzzy_rules = [\n", " rule1,\n", " rule2,\n", @@ -808,7 +741,7 @@ " return fuzzy_sys.output[\"pos\"]\n", "\n", "from sklearn.model_selection import train_test_split\n", - "#РАЗДЕЛИТЬ ДАТАСЕТ НА ОБУЧАЮЩУЮ, ТЕСТОВУЮ ВЫБОРКИ\n", + "\n", "#Тестирование нечеткой системы на тестовой выборке\n", "# Разделение данных на обучающую и тестовую выборки\n", "X = df[['user_reviews', 'price_original']]\n", @@ -862,6 +795,13 @@ "\n", "Возможно, что распределение отношений положительных отзывов к отрицательным имеет скорее случайный характер, поэтому оно не может быть описано с хорошей точностью нечёткими правилами" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "P.S. Было сделано более 5 попыток улучшить показатели засчёт изменения графиков функций и правил, но коэф. детерминации каждый раз всё равно был отрицательным (ещё больше по модулю, чем в данный момент)" + ] } ], "metadata": {