Created
November 6, 2018 04:46
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| def train_test(df, response_col='price', dummy_na=False, test_size=.3, rand_state=42, plot=False): | |
| #Split into explanatory and response variables | |
| X = df.drop(response_col, axis=1) | |
| y = df[response_col] | |
| X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, random_state=rand_state) | |
| lm_model = LinearRegression(normalize=True) | |
| lm_model.fit(X_train, y_train) | |
| train_preds = lm_model.predict(X_train) | |
| test_preds = lm_model.predict(X_test) | |
| train_score = r2_score(y_train, train_preds) | |
| test_score = r2_score(y_test, test_preds) | |
| return test_score, train_score, lm_model, X_train, X_test, y_train, y_test, test_preds |
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