Python MLP分类拟合
我是机器学习新手,我正在开发一个python应用程序,它使用一个数据集对扑克手进行分类,我将发布一些代码片段。它似乎不太管用。我得到了以下错误:Python MLP分类拟合,python,machine-learning,scikit-learn,neural-network,sklearn-pandas,Python,Machine Learning,Scikit Learn,Neural Network,Sklearn Pandas,我是机器学习新手,我正在开发一个python应用程序,它使用一个数据集对扑克手进行分类,我将发布一些代码片段。它似乎不太管用。我得到了以下错误: Traceback (most recent call last): File "C:\Users\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code exec(code_obj, self.user_global_ns,
Traceback (most recent call last):
File "C:\Users\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-62-0d21cd839ce4>", line 1, in <module>
mlp.fit(X_test, y_train.values.reshape(len(y_train), 1))
File "C:\Users\Anaconda3\lib\site-packages\sklearn\neural_network\multilayer_perceptron.py", line 618, in fit
return self._fit(X, y, incremental=False)
File "C:\Users\Anaconda3\lib\site-packages\sklearn\neural_network\multilayer_perceptron.py", line 330, in _fit
X, y = self._validate_input(X, y, incremental)
File "C:\Users\Anaconda3\lib\site-packages\sklearn\neural_network\multilayer_perceptron.py", line 902, in _validate_input
multi_output=True)
File "C:\Users\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 531, in check_X_y
check_consistent_length(X, y)
File "C:\Users\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 181, in check_consistent_length
" samples: %r" % [int(l) for l in lengths])
ValueError: Found input variables with inconsistent numbers of samples: [6253, 18757]
X_列的形状是18757,10,y_列的形状是18757,
我试过使用下面的帖子
y_train.values.reshape(len(y_train), 1)
但我还是犯了同样的错误。一些指导会有很大帮助,因为我不确定形状有什么问题
数据段:
您正在安装X_测试,而不是X_火车
y_train.values.reshape(len(y_train), 1)
mlp.fit(X_train, y_train.values.reshape(len(y_train), 1))