Re: [scikit-learn] Retracting model from the 'blackbox' SVM

The coef_ available from LinearSVC will be somewhat indicative of the relative importance of each feature. But you might want to look into our feature selection documentation: http://scikit-learn.org/stable/modules/feature_selection.html ___ scikit-learn

Re: [scikit-learn] Jeff Levesque: neuroscience related datasets

also (sorry for spamming the list!) should have said the Allen Institute has a ton of data: https://www.nwb.org/allen-cell-types-database/ and check out the cool dataset with this paper: https://figshare.com/articles/Recordings_of_ten_thousand_neurons_in_visual_cortex_during_spontaneous_behaviors/

Re: [scikit-learn] Jeff Levesque: neuroscience related datasets

Hi Jeffrey, check out these here for neuron data and fmri: http://crcns.org/ And the ones here for fmri: https://openfmri.org/ You can get started by installing one of the following packages and using their dataset downloaders http://nilearn.github.io/modules/reference.html#module-nilearn.datas

Re: [scikit-learn] Jeff Levesque: neuroscience related datasets

Hi Jeff, here's a couple of places to start, I'm sure other people can recommend more: https://crcns.org/ https://www.nature.com/sdata/policies/repositories (see under Neuroscience) There's also the challenge that Gael just announced, predicting autism from brain imaging data: https://paris-sacla

[scikit-learn] Jeff Levesque: neuroscience related datasets

Hi guys, I want to perform some basic data analysis. Anyone have good recommendations where I can obtain free datasets. I was thinking of trying to do something related to neuroscience. But, kaggle doesn't have many datasets for this focus. Thank you, Jeff Levesque https://github.com/jeff1evesq

[scikit-learn] Announcing IMPAC: an IMaging-PsychiAtry Challenge, using data-science to predict autism from brain imaging

Dear colleagues, It is my pleasure to announce IMPAC: an IMaging-PsychiAtry Challenge, using data-science to predict autism from brain imaging. https://paris-saclay-cds.github.io/autism_challenge/ This is a machine-learning challenge on brain-imaging data to achieve the best prediction of autis

Re: [scikit-learn] Breiman vs. scikit-learn definition of Feature Importance

Hi, See also chapters 6 and 7 of http://arxiv.org/abs/1407.7502 for another point of view regarding the "issue" with feature importances. TLDR: Feature importances as we have them in scikit-learn (i.e. MDI) are provably **not** biased, provided trees are built totally at random (as in ExtraTrees w

Re: [scikit-learn] Breiman vs. scikit-learn definition of Feature Importance

+1 on the post pointed out by Jeremiah. On 5 May 2018 at 02:08, Johnson, Jeremiah wrote: > Faraz, take a look at the discussion of this issue here: > http://parrt.cs.usfca.edu/doc/rf-importance/index.html > > Best, > Jeremiah > = > Jeremiah W. Johnson, Ph.