先加载数据


import pandas as pd

# Load data
melbourne_file_path = '../input/melbourne-housing-snapshot/melb_data.csv'
melbourne_data = pd.read_csv(melbourne_file_path) 
# Filter rows with missing price values
filtered_melbourne_data = melbourne_data.dropna(axis=0)
# Choose target and features
y = filtered_melbourne_data.Price
melbourne_features = ['Rooms', 'Bathroom', 'Landsize', 'BuildingArea', 
                        'YearBuilt', 'Lattitude', 'Longtitude']
X = filtered_melbourne_data[melbourne_features]

回归模型评价指标MSE、RMSE、MAE、R-Squared

MSE （Mean Squared Error）叫做均方误差。看公式

[ frac{1}{m}sum _ { i=1 }^m (y_ i-hat{y_i})^2]

参考

Model Validation

模型评估指标参考

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