以下代码用于进行 KFold 验证，但我要训练模型，因为它抛出错误
ValueError: Error when checking target: expected dense_14 to have shape (7,) but got array with shape (1,)
我的目标变量有 7 个类。我正在使用LabelEncoder将类编码为数字。
通过看到此错误，如果我将其更改为MultiLabelBinarizer对类进行编码。我收到以下错误
ValueError: Supported target types are: ('binary', 'multiclass'). Got 'multilabel-indicator' instead.
以下是KFold验证的代码
skf = StratifiedKFold(n_splits=10, shuffle=True)
scores = np.zeros(10)
idx = 0
for index, (train_indices, val_indices) in enumerate(skf.split(X, y)):
print("Training on fold " + str(index+1) + "/10...")
# Generate batches from indices
xtrain, xval = X[train_indices], X[val_indices]
ytrain, yval = y[train_indices], y[val_indices]
model …