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你好,请问数据分为训练集、测试集。为什么代码里是分开标准化呀?也就是训练集自己最大最小归一化,测试集自己最大最小归一化,这样可以么?常见的不是应该训练集归一化fit,测试集直接transform么?
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您说得对,通常将训练集标准化以使其拟合,然后直接转换测试集。但是,在时间序列数据中,测试集可以有不同的范围。例如,训练集的模式在 80 - 100 之间,但测试集的模式在 60 - 80 之间,因此在这种情况下,您应该使用测试集平均值和标准差来更好地拟合它。
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谢谢您的回复。还有一个问题,每次运行结果都略有不同。计算的loss,mae,r2_keras也随之改变。这样比如和其他方法比较的时候会有问题,请问有什么处理方法么?
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你好,请问数据分为训练集、测试集。为什么代码里是分开标准化呀?也就是训练集自己最大最小归一化,测试集自己最大最小归一化,这样可以么?常见的不是应该训练集归一化fit,测试集直接transform么?
The text was updated successfully, but these errors were encountered: