Question

我将1dCNN用于时间序列数据，但是在model.fit line中发生以下错误。错误如下：

Error when checking input: expected conv1d_11_input to have shape (6700, 1) but got array with shape (1, 1)。

任何一位PLZ帮助代码部分如下

    dataframe = pd.read_excel("file path", header=None,delim_whitespace=True)
    dataset = dataframe.values
    X=dataframe.values[:,0]
    Y=dataframe.values[:,2]
    X = np.expand_dims(X, axis=1)
    Y = np.expand_dims(Y, axis=1)
    (X_train, X_test, Y_train, Y_test) = train_test_split(X, Y, test_size=0.33, random_state=seed)
    X_train = np.reshape(X_train, (-1, X_train.shape[1],1))
    Y_train = np.reshape(Y_train, (Y_train.shape[0], 1, Y_train.shape[1]))
    X_test = np.reshape(X_test, (X_test.shape[0], 1, X_test.shape[1]))
    print(X_train.shape)
    print(Y_train.shape)
    n_timesteps, n_features, n_outputs = X_train.shape[0], X_train.shape[1], Y_train.shape[1]
    verbose, epochs, batch_size = 0, 100, 32
    model = Sequential()
    model.add(Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(n_timesteps,1)))
    model.add(Conv1D(filters=64, kernel_size=3, activation='relu'))
    model.add(Dropout(0.5))
    model.add(MaxPooling1D(pool_size=2))
    model.add(Flatten())
    model.add(Dense(100, activation='relu'))
    model.add(Dense(n_outputs, activation='softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
    model.summary()
    model.fit(X_train, Y_train, epochs=epochs, batch_size=batch_size, verbose=verbose)'

Answer 1

使用：

.tiff

检查输入时出错：预期conv1d_11_input具有形状（6700，1），但得到形状为（1，1）的数组

1 个答案: