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lab4

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Тукаева Альфия 2025-01-08 18:22:03 +04:00
parent 595a505c62
commit 8c645b301b
9 changed files with 2158 additions and 106 deletions
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3
.idea/.gitignore vendored
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# Default ignored files
/shelf/
/workspace.xml

12
.idea/ckmai.iml
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<?xml version="1.0" encoding="UTF-8"?>
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$" />
<orderEntry type="inheritedJdk" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
<component name="PyDocumentationSettings">
<option name="format" value="NUMPY" />
<option name="myDocStringFormat" value="NumPy" />
</component>
</module>

13
.idea/inspectionProfiles/Project_Default.xml
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<component name="InspectionProjectProfileManager">
<profile version="1.0">
<option name="myName" value="Project Default" />
<inspection_tool class="PyInterpreterInspection" enabled="false" level="WARNING" enabled_by_default="false" />
<inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
<option name="ignoredIdentifiers">
<list>
<option value="str.__pos__" />
</list>
</option>
</inspection_tool>
</profile>
</component>

6
.idea/inspectionProfiles/profiles_settings.xml
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<component name="InspectionProjectProfileManager">
<settings>
<option name="USE_PROJECT_PROFILE" value="false" />
<version value="1.0" />
</settings>
</component>

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.idea/modules.xml
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/ckmai.iml" filepath="$PROJECT_DIR$/.idea/ckmai.iml" />
</modules>
</component>
</project>

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.idea/vcs.xml
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="" vcs="Git" />
</component>
</project>

8
.idea/workspace.xml Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="PropertiesComponent">{
&quot;keyToString&quot;: {
&quot;last_opened_file_path&quot;: &quot;C:/Users/Альфия/PycharmProjects&quot;
}
}</component>
</project>

2149
lab4.ipynb Normal file
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59
src/utils.py
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import math
from typing import Dict, Tuple
import numpy as np
import pandas as pd
from pandas import DataFrame
from sklearn import metrics
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
def split_stratified_into_train_val_test(
@ -82,57 +79,3 @@ def split_stratified_into_train_val_test(
assert len(df_input) == len(df_train) + len(df_val) + len(df_test)
return df_train, df_val, df_test, y_train, y_val, y_test
def run_classification(
model: Pipeline,
X_train: DataFrame,
X_test: DataFrame,
y_train: DataFrame,
y_test: DataFrame,
) -> Dict:
result = {}
y_train_predict = model.predict(X_train)
y_test_probs = model.predict_proba(X_test)[:, 1]
y_test_predict = np.where(y_test_probs > 0.5, 1, 0)
result["pipeline"] = model
result["probs"] = y_test_probs
result["preds"] = y_test_predict
result["Precision_train"] = metrics.precision_score(y_train, y_train_predict)
result["Precision_test"] = metrics.precision_score(y_test, y_test_predict)
result["Recall_train"] = metrics.recall_score(y_train, y_train_predict)
result["Recall_test"] = metrics.recall_score(y_test, y_test_predict)
result["Accuracy_train"] = metrics.accuracy_score(y_train, y_train_predict)
result["Accuracy_test"] = metrics.accuracy_score(y_test, y_test_predict)
result["ROC_AUC_test"] = metrics.roc_auc_score(y_test, y_test_probs)
result["F1_train"] = metrics.f1_score(y_train, y_train_predict)
result["F1_test"] = metrics.f1_score(y_test, y_test_predict)
result["MCC_test"] = metrics.matthews_corrcoef(y_test, y_test_predict)
result["Cohen_kappa_test"] = metrics.cohen_kappa_score(y_test, y_test_predict)
result["Confusion_matrix"] = metrics.confusion_matrix(y_test, y_test_predict)
return result
def run_regression(
model: Pipeline,
X_train: DataFrame,
X_test: DataFrame,
y_train: DataFrame,
y_test: DataFrame,
) -> Dict:
result = {}
y_train_pred = model.predict(X_train.values)
y_test_pred = model.predict(X_test.values)
result["fitted"] = model
result["train_preds"] = y_train_pred
result["preds"] = y_test_pred
result["RMSE_train"] = math.sqrt(metrics.mean_squared_error(y_train, y_train_pred))
result["RMSE_test"] = math.sqrt(metrics.mean_squared_error(y_test, y_test_pred))
result["RMAE_test"] = math.sqrt(metrics.mean_absolute_error(y_test, y_test_pred))
result["R2_test"] = metrics.r2_score(y_test, y_test_pred)
return result