Re: [Scikit-learn-general] Univariate feature selection with hyperparameter estimation on a neuroimaging dataset with scikit

samples for each of the 10 outer folds? 2) How big should be the biggest C in the grid search? 3) Is there a way to retrieve the weights of the "outer" fold(s) ? I tried with documentation, but I was unsuccessful BestLudovico From: ludo25...@hotmail.com To: scikit-learn-general@

[Scikit-learn-general] Univariate feature selection with hyperparameter estimation on a neuroimaging dataset with scikit

Hi guys, I am new to Python and scikit learn package so I hope someone can help me.For my master thesis I am analyzing a neuroimaging dataset. I have 24 subjects divided in two classes (12 subjects each) that I would like to classify. My idea is to use "SelectKBest"

Re: [Scikit-learn-general] Univariate feature selection

Hi Josh. You are right. See this issue: https://github.com/scikit-learn/scikit-learn/issues/1149?source=cc Andy -- Get 100% visibility into Java/.NET code with AppDynamics Lite! It's a free troubleshooting tool designed

[Scikit-learn-general] Univariate feature selection

I am looking into the univariate selection example: http://scikit-learn.org/stable/auto_examples/plot_feature_selection.html#example-plot-feature-selection-py and noticed that the introduction to the example reads: " In the total set of features, only the 4 first ones are significant. We can see t