After some though about this problem today, I think it is an objective
function minimization problem, when the objective function can be the root
mean square deviation (RMSD) between the affinities of the common molecules
in the two data sets. I could work iteratively, first rescale and fit assa
Use the functiontransformer and create a function which make your transform using lasso
If you want to use lasso for feature selection in a pipeline you have to
wrap it in SelectFromModel.
On 09/06/2017 11:56 AM, Lefevre, Augustin wrote:
Hi all,
I am playing with the pipeline features of sklearn and it seems that I
can’t use a prediction algorithm as intermediate step.
For i
Hi all,
I am playing with the pipeline features of sklearn and it seems that I can't
use a prediction algorithm as intermediate step.
For instance, in the example below I use the output of a lasso as an additional
feature to feed a random forest, in such a way that feature selection the Lasso
d
Scikit-learn recently supported discretization(KBinsDiscretizer, see discrete
branch) and we need an example to illustrate the usage of it. I have proposed a
draft in https://github.com/scikit-learn/scikit-learn/issues/9339:(1)use the
iris dataset (only use two features)(2)plot the data before a
