8000 FIX: test_oob_score_regression by glouppe · Pull Request #2 · ndawe/scikit-learn · GitHub
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FIX: test_oob_score_regression #2

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Merged
merged 1 commit into from
Dec 7, 2012
Merged

FIX: test_oob_score_regression #2

merged 1 commit into from
Dec 7, 2012

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glouppe
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@glouppe glouppe commented Dec 7, 2012

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@ndawe
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ndawe commented Dec 7, 2012

Thanks!

ndawe
ndawe reviewed Dec 7, 2012
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sklearn/ensemble/forest.py
@@ -691,7 +691,7 @@ def score(self, X, y, sample_weight=None):
-------
z : float
"""
weighted_r2_score(y, self.predict(X), weights=sample_weight)
return weighted_r2_score(y, self.predict(X), weights=sample_weight)
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:)

ndawe added a commit that referenced this pull request Dec 7, 2012
@ndawe
Merge pull request #2 from glouppe/treeweights
b7955d3 
FIX: test_oob_score_regression
@ndawe ndawe merged commit b7955d3 into ndawe:treeweights Dec 7, 2012
ndawe pushed a commit that referenced this pull request Oct 13, 2017
@sergeyf @amueller
[MRG+2] Adding return_std options for models in linear_model/bayes.py (…
67a85b8 
…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 #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
ndawe pushed a commit that referenced this pull request Oct 13, 2017
@glemaitre @GaelVaroquaux
[MRG+1] QuantileTransformer (scikit-learn#8363)
26a1027 
* 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
ndawe pushed a commit that referenced this pull request Oct 13, 2017
@Henley13 @MechCoder
[MRG+1] _preprocess_data consistent with fused types (scikit-learn#9093)
89962f0 
* add test for _preprocess_data and make it consistent

* fix pep8

* add doc, cast systematically y in X.dtype and update test_coordinate_descent.py

* test if input values don't change with copy=True

* test if input values don't change with copy=True #2

* fix doc

* fix doc #2

* fix doc #3
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@glouppe @ndawe
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