ValueError:
class_weight
must contain all classes in the data. The classes {1, 2, 3} exist in the data but not inclass_weight
我正在尝试为我的不平衡类分配类权重,但在 model.fit() 之后它会生成此错误,尽管我看到已经针对此问题提供了其他解决方案但仍然无法解决它。
test_split=round(n*2/3)
x_train=x[:test_split]
y_train=y[:test_split]
x_test=x[test_split:]
y_test=y[test_split:]
class_weight_list = compute_class_weight('balanced', numpy.unique(y_train), y_train)
class_weight = dict(zip(numpy.unique(y_train), class_weight_list))
x_train=x_train.astype('float64')
x_test=x_test.astype('float64')
x_train/=255
x_test/=255
y_train=keras.utils.to_categorical(y_train, num_classes)
y_test=keras.utils.to_categorical(y_test, num_classes)
hist=model.fit(x_train, y_train,
batch_size=batch_size,
epochs=epochs,
validation_data=(x_test, y_test),
callbacks=[checkpoint],
class_weight=class_weight
)
最佳答案
先尝试标签编码
编辑
encoder = LabelEncoder()
encoder.fit(y_train)
y_train= encoder.transform(y_train)
y_test= encoder.transform(y_test)
class_weight_list = compute_class_weight('balanced', numpy.unique(y_train), y_train)
class_weight = dict(zip(numpy.unique(y_train), class_weight_list))
y_train=keras.utils.to_categorical(y_train, num_classes)
关于python - ValueError : `class_weight` must contain all classes in the data. 类{1,2,3}存在于数据中但不存在于 `class_weight`,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/49031309/