Keras CNN with 1D data | 易学教程

问题

Every instance of my data is an array with 72 elements. I am trying to construct a 1D cnn to do some classification but I got this error: Error when checking target: expected dense_31 to have 3 dimensions, but got array with shape (3560, 1)

This is my code:

training_features = np.load('features.npy')
training_labels = np.load('labels.npy')
training_features = training_features.reshape(-1, 72, 1)

model = Sequential()
model.add(Conv1D(64, 3, activation='relu', input_shape=(72, 1)))
model.add(MaxPooling1D(2))
model.add(Conv1D(64, 3, activation='relu'))
model.add(MaxPooling1D(2))
model.add(Dense(64, activation='relu'))
model.add(Dense(28, activation='softmax'))

model.compile(Adam(lr=.0001), loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(training_features, training_labels, batch_size=32, epochs=3, validation_split=0.1)

I am a beginner. Sorry if I have poor understanding.

回答1:

Check whether your inputs in correct form. Can you share the two *.npy files (or at least shapes of your inputs).

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv1D, Dense, MaxPooling1D, Flatten
from tensorflow.keras.optimizers import Adam

model = Sequential()
model.add(Conv1D(64, 3, activation='relu', input_shape=(72, 1)))
model.add(MaxPooling1D(2))
model.add(Conv1D(64, 3, activation='relu'))
model.add(MaxPooling1D(2))
model.add(Flatten())
model.add(Dense(64, activation='relu'))
model.add(Dense(28, activation='softmax'))

model.compile(Adam(lr=.0001), loss='categorical_crossentropy', metrics=['accuracy'])
#model.fit(training_features, training_labels, batch_size=32, epochs=3, validation_split=0.1)

model.summary()

Model: "sequential_4"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv1d_7 (Conv1D)            (None, 70, 64)            256       
_________________________________________________________________
max_pooling1d_6 (MaxPooling1 (None, 35, 64)            0         
_________________________________________________________________
conv1d_8 (Conv1D)            (None, 33, 64)            12352     
_________________________________________________________________
max_pooling1d_7 (MaxPooling1 (None, 16, 64)            0         
_________________________________________________________________
flatten (Flatten)            (None, 1024)              0         
_________________________________________________________________
dense_4 (Dense)              (None, 64)                65600     
_________________________________________________________________
dense_5 (Dense)              (None, 28)                1820      
=================================================================
Total params: 80,028
Trainable params: 80,028
Non-trainable params: 0
_________________________________________________________________

Hope this helps. Thanks!

回答2:

The problem is that you start with a three dimensional layer but never reduce the dimensionality in any of the following layers. Try adding model.add(Flatten()) before the first Dense layer.

来源：https://stackoverflow.com/questions/61030068/keras-cnn-with-1d-data

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python

tensorflow

keras

CNN