在将 Pandas 数据帧列传递给 scikit learn regressor 之前，是否应该以某种方式对其进行转换? [英] Should a pandas dataframe column be converted in some way before passing it to a scikit learn regressor?

问题描述

我有一个 Pandas 数据框并将 df[list_of_columns] 作为 X 和 df[[single_column]] 作为 Y 传递给随机森林回归器.

I have a pandas dataframe and passing df[list_of_columns] as X and df[[single_column]] as Y to a Random Forest regressor.

以下警告是什么意思，应该怎么做才能解决?

What does the following warnning mean and what should be done to resolve it?

DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().   probas = cfr.fit(trainset_X, trainset_Y).predict(testset_X)

推荐答案

只需检查你的 Y 变量的形状，它应该是一个一维对象，你可能传递了更多的东西(可能是微不足道的)维度.将其重塑为列表/一维数组的形式.

Simply check the shape of your Y variable, it should be a one-dimensional object, and you are probably passing something with more (possibly trivial) dimensions. Reshape it to the form of list/1d array.

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