Hi all,
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:
*fit(X, y)*
Fit the model to data matrix X and target y.
*Parameters:*
*X : *{array-like, sparse matrix}, shape (n_samples, n_features)
The input data.
*y : *array-like, shape (n_samples,)
The target values.
*Returns:*
self : returns a trained MLP model.
We can see that Y should be a column matrix. Does this mean Scikit-learn
doesn't support multiple outputs?
I am getting MemoryError when I try to fit now.
More: http://stackoverflow.com/questions/40945791/
memoryerror-in-scikit-learn
Please help.
Thanks!
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