Keras Conv1D: error of dimensions

Question

I am trying to perform a rating using the CNN template.

I have 150 classes. My train base has 19470 rows and 1945 columns. It is an matrix that contains 0 and 1.

import keras
from keras.models import Sequential
from keras.layers import Conv1D
from keras.layers.advanced_activations import LeakyReLU

model = Sequential()
model.add(Conv1D(150,kernel_size=3,input_shape(19470,1945),activation='linear',padding='same'))
model.add(LeakyReLU(alpha=0.1))



model.compile(loss=keras.losses.categorical_crossentropy, optimizer=keras.optimizers.Adam(),metrics=['accuracy'])

model.fit(x_train, y_train)

This raises:

ValueError: Error when checking input: expected conv1d_39_input to have 3 dimensions, but got array with shape (19470, 1945)

Possible duplicate of [Dimension of shape in conv1D](https://stackoverflow.com/questions/43396572/dimension-of-shape-in-conv1d) — benjaminplanche, Apr 06 '18 at 16:12

score 1 · Answer 1 · answered Jun 29 '18 at 22:43

Did you check your xtrain shape?

According to the error that keras is raising you should do: x_train = xtrain.reshape(19470, 1945, 1)

I don't understand why are you using as many layers of conv1d as classes you have? I can't give advice on the architecture of your NN, but I your last layer should be a Dense layer with 150 units and softmax activation. Don't you have 150 classes?

Keras Conv1D: error of dimensions

1 Answers1