[MRG] ENH: Support centering in LogisticRegression #1
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By default, files starting with _ and setup.py are ignored by nose. This causes doctests to be skipped in _*.py modules.
added link to sclera.metrics.make_scorer
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@lanzagar, please provide preliminary review. I don't know what I'm doing. 😆 |
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[MRG+1] Fix: FeatureHasher now accepts string values
[MRG+1] Fix to documentation and docstring of randomized lasso and randomized logistic regression
…weak [MRG+1] Do not ignore files starting with _ and . in nose
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[MRG] Fix broken link in ABOUT
…r-and-remove-unused-variable-in-multiclass
[MRG] FIX Fix NameError ("estimator" not defined). Remove unused var "ind".
…_fix [MRG+1] LabelBinarizer single label case now works for sparse and dense case
Fixing minor typos and inconsistencies in logistic regression docs
Added the following things: * Test when the sum is not equal to one * Test the prediction in case of a large bias for one class * Test explicitely class_prior_ * Move the function to update the class prior in the GaussianNB class * Remove the updating of the class prior before to actually compute the mean and variance Address comments for PR scikit-learn#6180 - Correct the documentation Address comment PR#6180 - Improve the class prior initialisation and updating We modify the code to: * Initialisat self.class_prior_ with the different possibilities (class_prior given or not, fit_prior True or False) * Update self.class_prior_ only when no class_prior is given and than fit_prior is True Address comments PR scikit-learn#6180 - Remove useless line Fix the file according to PEP8 regulations Update the API to have only class_prior in GaussianNB Correct prior fitting using samples and not class number Change name of priors and correct the warning with division by zero Update the API Remove functions which were called only once Add additional test for part of the code which was not covered in GaussianNB Correct doc formatting Correct spelling
Error 404 in documentation section 2.7.1. Novelty Detection
[MRG+1] MAINT: Simplify n_features_to_select logic in RFECV
…mlight_file-support-sparse-y [MRG+1] Make dump_svmlight_file support sparse y (fixes scikit-learn#6301)
[MRG+2] Fix for issue scikit-learn#6352
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