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lacava / few

a feature engineering wrapper for sklearn
https://lacava.github.io/few
GNU General Public License v3.0
50 stars 22 forks source link

cross_val changes #29

Closed rgupta90 closed 7 years ago

rgupta90 commented 7 years ago

I am not sure which is the best approach, commenting out the previous code or removing it. Thus, commented as of now. Also, kept self._training_features and self._training_labels assigned as these are being used in functions in other python files, which are being called here.

coveralls commented 7 years ago

Coverage Status

Coverage increased (+2.08%) to 75.179% when pulling 75ccde7dfb1b05c1e883b8330f3a76b561715f70 on cross_val into 7ba5f630ba309b3d6f0183440c78382dbeb70ea1 on master.

rgupta90 commented 7 years ago

self._training_features is used in population.py in line 235 which is called in few.py line 50

few.py line 50 self.pop = self.init_pop(x_t.shape[0])

population.py line 235 for i,p in it.zip_longest( range(self._training_features.shape[1]), pop.individuals,fillvalue=None):

coveralls commented 7 years ago

Coverage Status

Coverage increased (+2.08%) to 75.179% when pulling 39e93238ce7982701872314c50fefb65d43e6a87 on cross_val into 7ba5f630ba309b3d6f0183440c78382dbeb70ea1 on master.

lacava commented 7 years ago

ok, let's leave _training_features in for now then.