python-3.x - 断言错误: Mismatch between dataset size and units in output layer

Question

我想使用 scikit-neuralnetwork 进行 NN 分类，我有 5 个类，因此在输出层中，我的单位=5 但我收到此错误:数据集大小与输出层中的单位不匹配，我根据文档 reshape 了 y_train 并将“Sigmoid”函数应用于输出层: http://scikit-neuralnetwork.readthedocs.io/en/latest/guide_model.html#classification

If you want to do multi-label classification, simply fit using a y array of integers that has multiple dimensions, e.g. shape (N, 3) for three different classes. Then, make sure the last layer is Sigmoid instead.

y_train 形状为:(2115, 5)X_train 形状为:(2115, 343)这是代码:

import sknn.mlp as mlp
from sknn.mlp import Classifier
ip_layer = mlp.Layer('Sigmoid', units=1)
hidden_layer = mlp.Layer('Tanh', units=100)
op_layer = mlp.Layer('Sigmoid', units=5) 

nn = Classifier(
    [ip_layer, hidden_layer, op_layer],
    n_iter=10000
)
nn.fit(X_train, y_train)

Answer 1

输入层有一个单元。

如果您设置ip_layer = mlp.Layer('Sigmoid',units=343)它应该可以工作。