One dimensional data with CNN

Question

Just wondering whether anybody has done this? I have a dataset that is one dimensional (not sure whether it\'s the right word choice though). Unlike the usual CNN inputs whi

Answer 1

If your data were spatially related (you said it isn't) then you'd feed it to a convnet (or, specifically, a conv2d layer) with shape 1xNx1 or Nx1x1 (rows x cols x channels).

If this isn't spatial data at all - you just have N non-spatially-related features, then the shape should be 1x1xN.

For completeness, I should point out that if your data really is non-spatial, then there's really no point in using a convolutional layer/net. You could shape it as 1x1xN and then use 1x1 convolutions, but since a 1x1 convolution does the exact same thing as a fully-connected (aka dense aka linear) layer, you might as well just use that instead.