[scikit-learn] meta-estimator for multiple MLPRegressor

[Thomas Evangelidis]

On 8 January 2017 at 00:04, Jacob Schreiber <jmschreiber91 at gmail.com> wrote:

> If you have such a small number of observations (with a much higher
> feature space) then why do you think you can accurately train not just a
> single MLP, but an ensemble of them without overfitting dramatically?
>
>
>
​Because the observations in the data set don't differ much between them​.
To be more specific, the data set consists of a congeneric series of
organic molecules and the ebservation is their binding strength to a target
protein. The idea was to train predictors that can predict the binding
strenght of new molecules that belong to the same congeneric series.
Therefore special care is taken to apply the predictors to the right domain
of applicability. According to the literature, the same strategy has been
followed in the past several times. The novelty of my approach stems from
other factors that are irrelevant to this thread.


-- 

======================================================================

Thomas Evangelidis

Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic

email: tevang at pharm.uoa.gr

          tevang3 at gmail.com


website: https://sites.google.com/site/thomasevangelidishomepage/
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