Skip to content

[WIP] ENH: SMOTE for pure categorical data #565

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 8 commits into from
Closed

[WIP] ENH: SMOTE for pure categorical data #565

Changes from 1 commit
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
d1ac5bd
Add SMOTE for pure categorical data
ThomasKluiters May 5, 2019
e17ba76
Fix PEP issues
ThomasKluiters May 5, 2019
5f1ca14
Fix failing tests
ThomasKluiters May 5, 2019
c2fc4da
Fix doctest error
ThomasKluiters May 5, 2019
9db1071
Change order of counter keys in docstring
ThomasKluiters May 5, 2019
c2fe8c2
Rephrase docstring
ThomasKluiters May 5, 2019
bc96223
Refactor SMOTEN and SMOTENC to be more unified
ThomasKluiters May 7, 2019
c7e7036
Add documentation for SMOTEN
ThomasKluiters May 7, 2019
File filter

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
Fix PEP issues
  • Loading branch information
@ThomasKluiters
ThomasKluiters committed May 5, 2019
commit e17ba76ad9c39a96b34c8ec80cedebe3b156ebc7
10 changes: 5 additions & 5 deletions imblearn/over_sampling/_smote.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1214,10 +1214,10 @@ class SMOTEN(SMOTE):
def __init__(self, sampling_strategy='auto',
random_state=None, k_neighbors=5, n_jobs=1):
super(SMOTEN, self).__init__(sampling_strategy=sampling_strategy,
random_state=random_state,
k_neighbors=k_neighbors,
ratio=None,
n_jobs=n_jobs)
random_state=random_state,
k_neighbors=k_neighbors,
ratio=None,
n_jobs=n_jobs)

@staticmethod
def _check_X_y(X, y):
Expand Down Expand Up @@ -1261,7 +1261,7 @@ def _generate_sample(self, X, nn_data, nn_num, row, col, step):
"""
rng = check_random_state(self.random_state)
sample = super(SMOTEN, self)._generate_sample(X, nn_data, nn_num,
row, col, step)
row, col, step)
# To avoid conversion and since there is only few samples used, we
# convert those samples to dense array.
sample = (sample.toarray().squeeze()
Expand Down