title: Convolutional neural network Conv1d input shape
body: <p>I am trying to create a CNN to classify data. My Data is X[N_data, N_features]
  I want to create a neural net capable of classifying it. My problem is concerning the input shape of a Conv1D for the keras back end. </p>
  
  <p>I want to repeat a filter over.. let say 10 features and then keep the same weights for the next ten features. 
  For each data my convolutional layer would create N_features/10 New neurones.
  How can i do so? What should I put in input_shape?  </p>
  
  <pre><code>def cnn_model():
  model = Sequential()                                               
  model.add(Conv1D(filters=1, kernel_size=10 ,strides=10,     
                    input_shape=(1, 1,N_features),kernel_initializer= 'uniform',      
                    activation= 'relu')) 
  model.flatten()
  model.add(Dense(N_features/10, init= 'uniform' , activation= 'relu' ))
  </code></pre>
  
  <p>Any advice?
  thank you!</p>