Changes to fixing #5774 (label clamping)#2
Merged
boechat107 merged 1193 commits intoboechat107:issue-5774from Jun 13, 2017
Merged
Changes to fixing #5774 (label clamping)#2boechat107 merged 1193 commits intoboechat107:issue-5774from
boechat107 merged 1193 commits intoboechat107:issue-5774from
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… behaviour (scikit-learn#8452) * FIX/DOC Improve documentation regarding non-determinitic tree behaviour * FIX correct max_features
- No need for `regr.predict(diabetes_X_test)` to run multiple times. - Use `sklearn.metrics.mean_squared_error`. - Use `sklearn.metrics.r2_score`, instead of `regr.score`, which runs `regr.predict` again.
* BUG: fix svd_solver validation in PCA.fit * TST: add test of pca svd_solver
* Modify plot_custom_kernel for matplotlib v2 comp Add `edgecolors` attribute in scatter plot for better visualization in matplotlib version 2 Issue: scikit-learn#8364 * Modify plot_oneclass.py for matplotlib v2 comp Add `edgecolors` attribute to scatter plot for better visualization in matplotlib version 2 Issue: scikit-learn#8364 * Modify plot_rbf_parameters for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_separating_hyperplane_unbalanced for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plo_svm_kernels for matplotlib v2 Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_svm_margin for matplotlib v2 comp Add `edgecolors` attribute to scatter plot for better visualization. Issue: scikit-learn#8364 * Modify plot_svm_nonlinear for matplotlib v2 Add `edgecolors` attribute to scatter plot for matplotlib version 2 compatibility Issue: scikit-learn#8364 * Modify file for remove flake8 error Remove extra white space. Issue: scikit-learn#8364
* add html-noplot and help message to make.bat * changed spaces to tab in make.bat help * changed all spaces to tabs in make.bat update
…8120) * Add _RepeatedSplits and RepeatedKFold class * Add RepeatedStratifiedKFold and doc for repeated cvs * Change default value of n_repeats * Change input parameters of repeated cv constructor to n_splits, n_repeats, random_state * Generate random states in split function rather than store it beforehand * Doc changes, inheriting RepeatedKFold, RepeatedStratifiedKFold from _RepeatedSplits and other review changes * Remove blank line, put testcases for deterministic split in loop and add StopIteration check in testcase * Using rng directly as random_state param to create cv instance and added a check for cvargs * Fix pep8 warnings * Changing default values for n_splits and n_repeats and add entry in changelog * Adding name to the feature * Missing space
[MRG+2] modify disadvantage
…weight_invariance in metrics/tests/test_common.py (scikit-learn#8537) * Separated tests for regression features in test_sample_weight_invariance * Fixed pep8 * Removed unecessary check for regression * Updated regression metrics * Joel's suggestions
…y in estimator_checks (scikit-learn#8253)
…mentation (scikit-learn#8548) * clarify role of the function and streamline introduction * added feature selection methods to see also * completed see also * fixed pep related formatting for flake8checks. * fixed extra whitespace flake8 problems, remaining failure is a copied see all line from another function, the line is over by a period, does not make sense to newline that. * one more whitespace * FIX small pep8 error.
Use pip rather than easy_install in copy_joblib.sh. Also need to remove joblib/testing.py to avoid pytest dependency.
* MAINT: use manylinux dev wheels for numpy / scipy Use daily manylinux wheels for numpy and scipy, instead of soon-to-be-discontinued per-commit Precise wheels. * BF: add back ATLAS install for ubuntu build entry scikit-learn can link against BLAS libraries still at the same location as they were duing numpy build.
…arison on == (scikit-learn#7970) * reintroduced isclose() and flake8 fixes to fixes.py * changed == 0.0 to isclose(...) * example changes * changed back to abs() < epsilon * flake8 convention on file * reverted flake8 fixes * reverted flake8 fixes (2) * np.finfo(np.float32).tiny instead of hard coded epsilon 1e-150 * reverted to 1e-150 * whats new modified
Remove OutlierDetectionMixin, which was only used by by EllipticEnvelope
Remove the eleven average precision score Add better tests.
* resurrect quantile scaler * move the code in the pre-processing module * first draft * Add tests. * Fix bug in QuantileNormalizer. * Add quantile_normalizer. * Implement pickling * create a specific function for dense transform * Create a fit function for the dense case * Create a toy examples * First draft with sparse matrices * remove useless functions and non-negative sparse compatibility * fix slice call * Fix tests of QuantileNormalizer. * Fix estimator compatibility * List of functions became tuple of functions * Check X consistency at transform and inverse transform time * fix doc * Add negative ValueError tests for QuantileNormalizer. * Fix cosmetics * Fix compatibility numpy <= 1.8 * Add n_features tests and correct ValueError. * PEP8 * fix fill_value for early scipy compatibility * simplify sampling * Fix tests. * removing last pring * Change choice for permutation * cosmetics * fix remove remaining choice * DOC * Fix inconsistencies * pep8 * Add checker for init parameters. * hack bounds and make a test * FIX/TST bounds are provided by the fitting and not X at transform * PEP8 * FIX/TST axis should be <= 1 * PEP8 * ENH Add parameter ignore_implicit_zeros * ENH match output distribution * ENH clip the data to avoid infinity due to output PDF * FIX ENH restraint to uniform and norm * [MRG] ENH Add example comparing the distribution of all scaling preprocessor (#2) * ENH Add example comparing the distribution of all scaling preprocessor * Remove Jupyter notebook convert * FIX/ENH Select feat before not after; Plot interquantile data range for all * Add heatmap legend * Remove comment maybe? * Move doc from robust_scaling to plot_all_scaling; Need to update doc * Update the doc * Better aesthetics; Better spacing and plot colormap only at end * Shameless author re-ordering ;P * Use env python for she-bang * TST Validity of output_pdf * EXA Use OrderedDict; Make it easier to add more transformations * FIX PEP8 and replace scipy.stats by str in example * FIX remove useless import * COSMET change variable names * FIX change output_pdf occurence to output_distribution * FIX partial fixies from comments * COMIT change class name and code structure * COSMIT change direction to inverse * FIX factorize transform in _transform_col * PEP8 * FIX change the magic 10 * FIX add interp1d to fixes * FIX/TST allow negative entries when ignore_implicit_zeros is True * FIX use np.interp instead of sp.interpolate.interp1d * FIX/TST fix tests * DOC start checking doc * TST add test to check the behaviour of interp numpy * TST/EHN Add the possibility to add noise to compute quantile * FIX factorize quantile computation * FIX fixes issues * PEP8 * FIX/DOC correct doc * TST/DOC improve doc and add random state * EXA add examples to illustrate the use of smoothing_noise * FIX/DOC fix some grammar * DOC fix example * DOC/EXA make plot titles more succint * EXA improve explanation * EXA improve the docstring * DOC add a bit more documentation * FIX advance review * TST add subsampling test * DOC/TST better example for the docstring * DOC add ellipsis to docstring * FIX address olivier comments * FIX remove random_state in sparse.rand * FIX spelling doc * FIX cite example in user guide and docstring * FIX olivier comments * EHN improve the example comparing all the pre-processing methods * FIX/DOC remove title * FIX change the scaling of the figure * FIX plotting layout * FIX ratio w/h * Reorder and reword the plot_all_scaling example * Fix aspect ratio and better explanations in the plot_all_scaling.py example * Fix broken link and remove useless sentence * FIX fix couples of spelling * FIX comments joel * FIX/DOC address documentation comments * FIX address comments joel * FIX inline sparse and dense transform * PEP8 * TST/DOC temporary skipping test * FIX raise an error if n_quantiles > subsample * FIX wording in smoothing_noise example * EXA Denis comments * FIX rephrasing * FIX make smoothing_noise to be a boolearn and change doc * FIX address comments * FIX verbose the doc slightly more * PEP8/DOC * ENH: 2-ways interpolation to avoid smoothing_noise Simplifies also the code, examples, and documentation
* DOC add hyperlink to example * Remove useless change * DOC fix hyperlink * DOC fix links
* Add deprecation message and test. * Adding performance warning and ignore_warnings in test * Add deprecation to whatsnew and remove LSHForest references from docs. Removing benchmark for lsh
…ll hierarchy (scikit-learn#9004) * FIX : remove n_nonzero_coefs from attr of LassoLarsCV + clean up call to Lars._fit * cleanup * fix deprecation warning + clarify warning * add test * pep8 * adddress comments
* fix OVR classifier edgecase bugs * add regression tests for OVO and OVR decision function shapes
… classifier (scikit-learn#9063) * FIX/TST revert scikit-learn#5802 and raise error for faulty classifier * FIX check_estimator take care of the rest
* correcting information criterion calculation in least_angle.py The information criterion calculation is not compatible with the original paper Zou, Hui, Trevor Hastie, and Robert Tibshirani. "On the “degrees of freedom” of the lasso." The Annals of Statistics 35.5 (2007): 2173-2192. APA * FIX : fix AIC/BIC computation in LassoLarsIC * update what's new * fix test * fix test * address comments * DOC comments and docstring on criterion computation
with sphinx 1.6
to fix pdf doc generation
Long commit messages can trigger a pager which is not what you want when running flake8_diff.sh in a terminal.
now that the sprint is over.
Owner
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Yes, it does look right to me! It's actually very close to my first proposal, but the tests were failing because of the new constructor with |
Author
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Well if you're happy to merge, I'll try get another reviewer (or perhaps
two) in.
…On 13 June 2017 at 21:34, Andre Boechat ***@***.***> wrote:
Yes, it does look right to me! It's actually very close to my first
proposal, but the tests were failing because of the new constructor with
alpha=None (line 353
<91b7f9a#diff-e94588a33277ed910f8f13bd27430544R353>),
complaining that alpha's default value was different of the one in the base
class. This doesn't seem to be the reason this time.
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…scikit-learn#7838) * initial commit for return_std * initial commit for return_std * adding tests, examples, ARD predict_std * adding tests, examples, ARD predict_std * a smidge more documentation * a smidge more documentation * Missed a few PEP8 issues * Changing predict_std to return_std #1 * Changing predict_std to return_std #2 * Changing predict_std to return_std scikit-learn#3 * Changing predict_std to return_std final * adding better plots via polynomial regression * trying to fix flake error * fix to ARD plotting issue * fixing some flakes * Two blank lines part 1 * Two blank lines part 2 * More newlines! * Even more newlines * adding info to the doc string for the two plot files * Rephrasing "polynomial" for Bayesian Ridge Regression * Updating "polynomia" for ARD * Adding more formal references * Another asked-for improvement to doc string. * Fixing flake8 errors * Cleaning up the tests a smidge. * A few more flakes * requested fixes from Andy * Mini bug fix * Final pep8 fix * pep8 fix round 2 * Fix beta_ to alpha_ in the comments
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Because I've merged with master it may be a bit hard to see the diff, but see 91b7f9a where my main changes reside. Does this look right to you?
Changes described in 69b3e89