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a guest Oct 12th, 2017 50 Never
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  1. from sklearn.linear_model import LinearRegression
  2. from sklearn.metrics import mean_absolute_error
  3. lr_model=LinearRegression()
  4. lr_model.fit(X_train,y_train)
  5. lr_predictions = lr_model.predict(X_test)
  6. mae = mean_absolute_error(y_test, lr_predictions)
  7. mae
  8. 16.029773809312484
  9.  
  10. from sklearn.ensemble import RandomForestRegressor
  11. rf_model=RandomForestRegressor(n_estimators=150, max_depth=5, min_samples_split=5)
  12. rf_model.fit(X_train,y_train)
  13. rf_predictions = rf_model.predict(X_test)
  14. mae = mean_absolute_error(y_test,rf_predictions)
  15. mae
  16. 365.7303688636672
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