Question

我正在尝试使用sknn.mlp为XOR问题训练MLP分类器

from sknn.mlp import Classifier, Layer
X=numpy.array([[0,1],[0,0],[1,0]])
print X.shape
y=numpy.array([[1],[0],[1]])
print y.shape
nn=Classifier(layers=[Layer("Sigmoid",units=2),Layer("Sigmoid",units=1)],n_iter=100)
nn.fit(X,y)

这导致：

No handlers could be found for logger "sknn"
Traceback (most recent call last):
File "xorclassifier.py", line 10, in <module>
nn.fit(X,y)
File "/usr/local/lib/python2.7/site-packages/sknn/mlp.py", line 343, in fit
return super(Classifier, self)._fit(X, yp)
File "/usr/local/lib/python2.7/site-packages/sknn/mlp.py", line 179, in _fit
X, y = self._initialize(X, y)
File "/usr/local/lib/python2.7/site-packages/sknn/mlp.py", line 37, in _initialize
self._create_specs(X, y)
File "/usr/local/lib/python2.7/site-packages/sknn/mlp.py", line 64, in _create_specs
"Mismatch between dataset size and units in output layer."
AssertionError: Mismatch between dataset size and units in output layer.

Answer 1

Scikit似乎将您的y向量转换为形状的二元向量（n_samples，n_classes）。在你的情况下，n_classes是两个。所以试试

nn=Classifier(layers=[Layer("Sigmoid",units=2),Layer("Sigmoid",units=2)],n_iter=100)

数据集大小中的scikit-neuralnetwork不匹配错误

1 个答案: