python之MSE、MAE、RMSE

发布时间:2019-08-29 07:38:30编辑:auto阅读(3570)

    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)
    print(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
    
    
    
    
    from math import sqrt
    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

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