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@jona-sassenhagen @agramfort @dengemann
On my computer, the `MultiTaskLasso` from sklearn seems to be unable to run parallel predictions (fit is fine though). I haven't run an investigation yet... D…
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Is it intended that, unlike `sklearn.cross_validation.check_cv` ([here](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/cross_validation.py#L1646)), `sklearn.model_selection.check_cv`…
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I am running a classification problem. The input is a file in ARFF format. The file works fine in Weka. The class distribution is a bit skewed. Is this a bug?
``` pytb
Traceback (most recent call la…
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According to @ogrisel
Needs investigation.
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Hello
My name is Iván, I'm stuck from several days ago with the problem I'm going to describe. I'm following the Daniel Nouri's tutorial about deep learning: http://danielnouri.org/notes/category/dee…
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All `cv` should say that the default is stratified for classification, and then a list of available objects is in the cross_validation module.
Currently, some say
> A cross-validation generator to us…
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In many situations, you don't have a test set so you would like to use CV for _both_ evaluation and hyper-parameter tuning. Therefore, you need to do nested cross-validation:
``` python
for train, te…
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``` julia
julia> (c, v, inds) = cross_validate(
inds -> compute_center(data[:, inds]), # training function
(c, inds) -> compute_rmse(c, data[:, inds]), # evaluation functio…
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The `grid_search` module now supports a list of grids, and a random-sampled parameter space, and may in the future support other search algorithms. The shared purpose is: tuning (or exploring) hyper-p…
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> > > import numpy as np; import eights as e; from sklearn.ensemble import RandomForestClassifierexp >>> e.operate.simple_clf(np.array([[1,1,1],[1,2,3]]), np.array([1,1,1]),RandomForestClassifier())
>…