MSE_MAE_RMSE.py

# _*_ coding: utf-8 _*_
# @Author   : daluzi
# @time     : 2019/10/8 16:15
# @File     : MSE_MAE_RMSE.py
# @Software : PyCharm
from math import sqrt

target = [1.5, 2.1, 3.3, -4.7, -2.3, 0.75]
prediction = [0.5, 1.5, 2.1, -2.2, 0.1, -0.5]

error = []
for i in range(len(target)):
	error.append(target[i] - prediction[i])

print("Errors: ", error)

squaredError = []
absError = []
for val in error:
	squaredError.append(val * val)  # target-prediction之差平方
	absError.append(abs(val))  # 误差绝对值

print("Square Error: ", squaredError)
print("Absolute Value of Error: ", absError)

print("MSE = ", sum(squaredError) / len(squaredError))  # 均方误差MSE

print("RMSE = ", sqrt(sum(squaredError) / len(squaredError)))  # 均方根误差RMSE
print("MAE = ", sum(absError) / len(absError))  # 平均绝对误差MAE

targetDeviation = []
targetMean = sum(target) / len(target)  # target平均值
for val in target:
	targetDeviation.append((val - targetMean) * (val - targetMean))
print("Target Variance = ", sum(targetDeviation) / len(targetDeviation))  # 方差

print("Target Standard Deviation = ", sqrt(sum(targetDeviation) / len(targetDeviation)))  # 标准差