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import os
import sys
import numpy as np
import pandas as pd
import pickle
from sklearn.metrics import r2_score
from src.logger import logging
from src.exception import CustomException
def save_object(file_path, obj):
try:
dir_path = os.path.dirname(file_path)
os.makedirs(dir_path,exist_ok=True)
with open(file_path, 'wb') as file_obj:
pickle.dump(obj,file_obj)
except Exception as e:
raise CustomException(e,sys)
def evaluate_models(X_train, y_train, X_test, y_test, models):
try:
report = {}
for i in range(len(list(models))):
model = list(models.values())[i]
logging.info('training started')
model.fit(X_train,y_train)
y_train_pred = model.predict(X_train)
y_test_pred = model.predict(X_test)
train_model_score = r2_score(y_train, y_train_pred)
test_model_score = r2_score(y_test,y_test_pred)
report[list(models.keys())[i]] = test_model_score
return report
except Exception as e:
raise ConnectionAbortedError(e,sys) |