Python 如何使用Scikit学习中的MLPClassizer创建神经网络，使用5 X输入和1 Y输出？

因此，我尝试使用Python中的神经网络将一组特性映射为一个值。基本上，我从csv中读取一些值，然后将它们插入分类器，错误不断发生。我对ML没有太多的经验，这个库对我来说是新的，所以任何帮助都将不胜感激

代码：

错误：

Traceback (most recent call last):
  File "analyzeTrainingData.py", line 13, in <module>
print (clf.fit(x,y))
  File "/usr/local/lib/python3.5/dist-packages/sklearn/neural_network/multilayer_perceptron.py", line 973, in fit
hasattr(self, "classes_")))
  File "/usr/local/lib/python3.5/dist-packages/sklearn/neural_network/multilayer_perceptron.py", line 331, in _fit
X, y = self._validate_input(X, y, incremental)
  File "/usr/local/lib/python3.5/dist-packages/sklearn/neural_network/multilayer_perceptron.py", line 910, in _validate_input
multi_output=True)
  File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py", line 542, in check_X_y
ensure_min_features, warn_on_dtype, estimator)
  File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py", line 410, in check_array
"if it contains a single sample.".format(array))
ValueError: Expected 2D array, got 1D array instead:

然后声明：

Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

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假设x是一个numpy数组，您正在创建一个N形向量，它不能作为训练数据输入。尝试printx.shape并查看它打印出的内容

如果要创建包含5列的矩阵，应使用np.appendx，

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[第[0]行、第[1]行、第[2]行、第[3]行、第[4]行]、指定的axis=0

是否编辑您的问题，并提供NN实现以及我们可能试图帮助您的错误？是的，很抱歉，我无意中点击了提交。

list(['237', '128', '352', '721.6', '11.275'])]

Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.