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Add sklearn.utils.check_array to fit and predict #53

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mpearmain opened this issue Jul 19, 2018 · 0 comments · May be fixed by #73
Open

Add sklearn.utils.check_array to fit and predict #53

mpearmain opened this issue Jul 19, 2018 · 0 comments · May be fixed by #73

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@mpearmain
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Currently the fit method fails if you pass a pandas dataframe object to the fit() and predict() adding using the sklearn util check_array (http://scikit-learn.org/stable/modules/generated/sklearn.utils.check_array.html#sklearn.utils.check_array) will by default convert the pandas df to an at 2D numpy array which can then be used without code change from the user.

i.e
In the examples you load data as a data frame

genetic_data = pd.read_csv('https://github.com/EpistasisLab/scikit-rebate/raw/master/data/'
                           'GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1.tsv.gz',
                           sep='\t', compression='gzip')
# 
# Now we convert to a numpy array
#
features, labels = genetic_data.drop('class', axis=1).values, genetic_data['class'].values

This would be as simple as changing (in fit() and 'predict()`)

 self._X = check_array(X)
 self._y = column_or_1d(y)
aadu added a commit to aadu/scikit-rebate that referenced this issue Aug 7, 2020
@aadu
Add support for pandas DataFrames - EpistasisLab#53
312566a
@aadu aadu linked a pull request Aug 7, 2020 that will close this issue
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Add support for pandas DataFrames aadu/scikit-rebate
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@mpearmain