Hi Everybody,
I have some IR techniques implemented in Python, and I want to contribute
to sklearn. But I am having some trouble with sparse data:
https://github.com/dvro/scikit-learn/blob/instance_reduction/sklearn/instance_reduction/enn.py
Here is one of the techniques (I'll improve the style latter), and when
testing I get
=================================================
ERROR: sklearn.tests.test_common.test_estimators_sparse_data
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
self.test(*self.arg)
File "/home/dayvid/workspace/scikit-learn/sklearn/tests/test_common.py",
line 145, in test_estimators_sparse_data
raise exc
ValueError: data type not understood
What is the best way to handle this issue. I thought about raising an
exception, but I do not think that's the case.
Thanks,
--
Dayvid Victor R. de Oliveira
MSc Candidate in Computer Science at Federal University of Pernambuco (UFPE)
BSc in Computer Engineering - Federal University of Pernambuco (UFPE)
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