我有一个600行和271列的数据集（最后一列包含类）。每行包含恶意软件功能及其类标签。我正在编写一个卷积神经网络代码来预测这些类。共有9个班级。以下是我的代码：
dataset = pd.read_csv('train.csv')
X = dataset.iloc[:, 0:270].values
y = dataset.iloc[:, 270].values
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20)
model = Sequential()
model.add(Convolution1D(64, 10, input_shape=(643,270)))
model.add(Activation('relu'))
model.add(MaxPooling1D(1))
model.add(Flatten())
model.add(Dense(100))
model.add(Dropout(0.5))
model.add(Dense(9))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy', optimizer = 'adam', metrics = ['accuracy'])
X_train = np.reshape(X_train, (1, X_train.shape[0], X_train.shape[1]))
X_test = np.reshape(X_test, (1, X_test.shape[0], X_test.shape[1]))
y_train = np_utils.to_categorical(y_train, 10)
y_test = np_utils.to_categorical(y_test, 10)
model.fit(X_train,y_train,validation_data=(X_test,y_test))
print(str(model.evaluate(x_test,y_test)))
我在这一行收到错误：
model.fit(X_train,y_train,validation_data=(X_test,y_test))
Error: Error when checking target: expected activation_2 to have shape (None, 9)
but got array with shape (643, 10)
因为＆＃34; y_train＆＃34;这种训练形式不合适。有人可以解释我如何解决这个问题并重塑y_train以获得成功的培训吗？
修改
将input_shape更改为第二和第三维形状后，错误现在更改为：
fValueError: Error when checking target: expected activation_2 to have shape (None, 1)
but got array with shape (643, 10)
请解决这个问题吗？ 谢谢！