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Tag: conv-neural-network

Error while running CNN for 1 dimensional data in R

I am trying to run 1 dimensional CNN in R using keras package. I am trying to create one-dimensional Convolutional Neural Network (CNN) architecture with the following specification But it is giving me following error Error in py_call_impl(callable, dots$args, dots$keywords) : ValueError: Negative dimension size caused by subtracting 4 from 1 for ‘conv1d_20/conv1d’ (op: ‘Conv2D’) with input shapes: [?,1,1,128], [1,4,128,256].

Input Shape for 1D CNN (Keras)

I’m building a CNN using Keras, with the following Conv1D as my first layer: I’m training with the function: In which train_df is a pandas dataframe of two columns where, for each row, label is an int (0 or 1) and payload is a ndarray of floats padded with zeros/truncated to a length of 1000. The total # of training

Keras CNN Error: expected Sequence to have 3 dimensions, but got array with shape (500, 400)

I’m getting this error: ValueError: Error when checking input: expected Sequence to have 3 dimensions, but got array with shape (500, 400) These are the below codes that I’m using. Output (here I’ve 500 rows in each): Code: Any insights? Answer Two things – Conv1D layer expects input to be in the shape (batch_size, x, filters), in your case (500,400,1).

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