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import os
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import sys
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import numpy as np
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import pandas as pd
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import dill
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import pickle
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from sklearn.metrics import r2_score
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from sklearn.model_selection import GridSearchCV
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from src.exception import CustomException
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def save_object(file_path, obj):
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try:
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dir_path = os.path.dirname(file_path)
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os.makedirs(dir_path, exist_ok=True)
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with open(file_path, "wb") as file_obj:
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pickle.dump(obj, file_obj)
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except Exception as e:
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raise CustomException(e, sys)
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def evaluate_models(X_train, y_train,X_test,y_test,models,param):
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try:
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report = {}
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for i in range(len(list(models))):
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model = list(models.values())[i]
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para=param[list(models.keys())[i]]
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gs = GridSearchCV(model,para,cv=3)
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gs.fit(X_train,y_train)
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model.set_params(**gs.best_params_)
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model.fit(X_train,y_train)
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y_train_pred = model.predict(X_train)
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y_test_pred = model.predict(X_test)
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train_model_score = r2_score(y_train, y_train_pred)
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test_model_score = r2_score(y_test, y_test_pred)
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report[list(models.keys())[i]] = test_model_score
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return report
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except Exception as e:
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raise CustomException(e, sys)
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def load_object(file_path):
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try:
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with open(file_path, "rb") as file_obj:
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return pickle.load(file_obj)
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except Exception as e:
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raise CustomException(e, sys) |
