[scikit-learn] Fwd: Scikit-learn MLPRegressor Help
t3kcit at gmail.com
Sat Dec 3 13:10:36 EST 2016
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
for image labeling (it looks like you have one label per pixel, not per
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