On 12/03/2016 05:29 AM, Gael Varoquaux wrote:
On Sat, Dec 03, 2016 at 03:08:00PM +0530, Alekh Karkada Ashok wrote:
I want use the Scikit-learn's MLPRegressor to map image to image. That is I
have a numpy array of size [1000,2030400] (1000 samples, 76800x3 (RGB) pixels).
Corresponding labelled images I have. Therefore Y is also [1000,230400]. But
according to documentation:
1 thousands samples and 2030 thousands features: you are using the wrong
tool, I multi-layer perceptron model will be too complex and overfit in
these settings. I would suggest a ridge.
These are images! Don't use ridge, use a convolutional neural network.
Our MLP is not convolutional, it will not be useful.
There is a lot of material out there on how to use covolutional neural
networks
for image labeling (it looks like you have one label per pixel, not per
image)
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