#🐍 #Python #評価指標 #回帰

evaluation_regresser-basic.py

# libraries
import numpy as np
from sklearn.metrics import r2_score # 決定係数(R^2)
from sklearn.metrics import mean_squared_error # 平均二乗誤差(MSE) 
from sklearn.metrics import mean_absolute_error # 平気絶対値誤差(MAE)


# ------------------------------
# 　途中式割愛 
# ------------------------------


print(f"R2スコア ： {r2_score(answer,　predict)}")
print(f"MSE : {mean_squared_error(answer,　predict)}")
print(f"MAE : {mean_absolute_error(answer,　predict)}")

#　二乗平方根誤差(RMSE)
mse = mean_squared_error(answer,　predict)
print("RMSE",np.sqrt(mse))