当期望1d数组时，传递了列向量y [英] A column-vector y was passed when a 1d array was expected

问题描述

我需要适应sklearn.ensemble中的RandomForestRegressor.

forest = ensemble.RandomForestRegressor(**RF_tuned_parameters)
model = forest.fit(train_fold, train_y)
yhat = model.predict(test_fold)

此代码始终有效，直到我对数据进行了一些预处理(train_y)为止. 错误消息显示:

This code always worked until I made some preprocessing of data (train_y). The error message says:

DataConversionWarning:当期望一个1d数组时，传递了列向量y.请将y的形状更改为(n_samples，)，例如使用ravel().

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().

model = forest.fit(train_fold，train_y)

model = forest.fit(train_fold, train_y)

以前，train_y是一个Series，现在是numpy数组(它是列向量).如果我应用train_y.ravel()，则它将成为行向量，并且不会出现错误消息，通过预测步骤需要花费很长时间(实际上，它永远不会完成...).

Previously train_y was a Series, now it's numpy array (it is a column-vector). If I apply train_y.ravel(), then it becomes a row vector and no error message appears, through the prediction step takes very long time (actually it never finishes...).

在RandomForestRegressor的文档中，我发现train_y应该定义为y : array-like, shape = [n_samples] or [n_samples, n_outputs] 知道如何解决这个问题吗?

In the docs of RandomForestRegressor I found that train_y should be defined as y : array-like, shape = [n_samples] or [n_samples, n_outputs] Any idea how to solve this issue?

推荐答案

更改此行:

model = forest.fit(train_fold, train_y)

收件人:

model = forest.fit(train_fold, train_y.values.ravel())

.values将给出数组中的值. (形状:(n，1)

.values will give the values in an array. (shape: (n,1)

.ravel会将数组形状转换为(n，)

.ravel will convert that array shape to (n, )

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