"predict_classes() takes from 2 to 4 positional arguments but 5 were given" 错了

Question

我在运行时收到此错误： TypeError: predict_classes() takes from 2 to 4 positional arguments but 5 were given 我对 python 不太熟悉，所以我不确定该怎么做。这是相关代码：

X = dataset[:, 0:4]
y = dataset[:, 4]
model = Sequential()
model.add(keras.layers.Dense(12, input_dim=4, activation='relu'))
model.add(keras.layers.Dense(8, activation='relu'))
model.add(keras.layers.Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(X, y, epochs=150, batch_size=10)
accuracy = model.evaluate(X, y)
print(accuracy)
MS = int(input('ms'))
RC = int(input('rc'))
LC = int(input('lc'))
KS = int(input('ks'))
predictions = model.predict_classes(MS, RC, LC, KS)
print(predictions)

Answer 1

您必须传递一个形状为 (1, 4) 的 numpy 数组，其中 1 是批量大小。

predictions = model.predict_classes(np.array([[MS, RC, LC, KS]]))
print(predictions[0])

"predict_classes() takes from 2 to 4 positional arguments but 5 were given" 错了

"predict_classes() takes from 2 to 4 positional arguments but 5 were given" erorr

python

keras

sequential