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标准化相同尺度的变量?

[英]Standardize same-scale variables?

thinking about a problem… should you standardize two predictors that are already on the same scale (say kilograms) but may have different ranges?考虑一个问题……您是否应该标准化两个已经处于相同尺度(例如千克)但可能具有不同范围的预测变量? The model is a KNN model 是一个 KNN

I think you should because the model will give the predictor eith the higher range more importance in calculating distance我认为您应该这样做,因为 model 会在计算距离时给予预测器更高的范围更重要

It is better to standardize the data even though being on same scale.即使规模相同,也最好将数据标准化。 Standardizing would reduce the distance (specifically euclidean) that would help weights to not vary much from the point intial to them.标准化会减少距离(特别是欧几里德),这将有助于权重从初始点到它们的变化不大。 Having huge seperated distance would rather have more calculation involved.拥有巨大的分离距离宁愿涉及更多的计算。 Also distance calculation done in KNN requires feature values to scaling is always prefered.此外,在 KNN 中完成的距离计算需要特征值来缩放总是首选。

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