我目前正在尝试训练 sklearn 中实现的 MLPClassifier…当我尝试使用给定的值进行训练时，我得到了以下错误：
ValueError: setting an array element with a sequence.
特征向量的格式是
[ [one_hot_encoded 品牌名称], [不同应用缩放到均值为0和方差为1] ]
有谁知道我做错了什么吗？
谢谢！
特征向量：
[
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]
g_a_group:
[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]
MLP:
from sklearn.neural_network import MLPClassifier
clf = MLPClassifier(solver=’lbfgs’, alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1)
clf.fit(feature_vectors, g_a_group)
回答：
从 scikit-learn 的角度来看，你的数据在 .fit 调用中没有任何意义。特征向量应该是一个大小为 N x d 的矩阵，其中 N 是数据点的数量，d 是特征的数量，而你的第二个变量应该保存标签，因此它应该是长度为 N 的向量（或 N x k，其中 k 是每个点输出/标签的数量）。无论你的变量代表什么，它们的大小都不符合它们应该代表的内容。
