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statistical_results.txt
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relative frequencies - 228969 issues
number of developers: 7914
number of selected developer: 21
number of selected issues: 57798
Train size 38724
Test size 19074
Number of features 144944
==============================================
adobejira 0.128655
davsclaus 0.026991
njiang 0.008984
aonishuk 0.006831
tabish121 0.006577
shazron 0.006433
aantonenko 0.005368
andrus 0.005311
atkach 0.005001
wesmckinn 0.004983
julianhyde 0.004852
andy.seaborne 0.004809
purplecabbage 0.004743
ababiichuk 0.004490
[email protected] 0.004485
djohnson 0.004276
jbellis 0.004223
ancosen 0.003992
elserj 0.003848
bowserj 0.003795 -----
onechiporenko 0.003782 --------
slebresne 0.003677
gtully 0.003586
jaimin 0.003533
akovalenko 0.003310
dsen 0.003262
rxin 0.003153
dmitriusan 0.003140
u39kun 0.003118
szetszwo 0.003083
=============================================
adobejira 29458
davsclaus 6180
njiang 2057
aonishuk 1564
tabish121 1506
shazron 1473
aantonenko 1229
andrus 1216
atkach 1145
wesmckinn 1141
julianhyde 1111
andy.seaborne 1101
purplecabbage 1086
ababiichuk 1028
[email protected] 1027
djohnson 979
jbellis 967
ancosen 914
elserj 881
bowserj 869 ----
onechiporenko 866 -----
slebresne 842
gtully 821
jaimin 809
akovalenko 758
dsen 747
rxin 722
dmitriusan 719
u39kun 714
szetszwo 706
Results
==========================================================================
accuracy
(micro)
(macro)
(weighted)
Naive bayes #####
0.8139351997483485
(0.8139351997483485, 0.8139351997483485, 0.8139351997483485, None)
(0.7814146457862783, 0.574919890303864, 0.6173828865979648, None)
(0.8363068749150396, 0.8139351997483485, 0.7950237649377736, None)
Logistic Regression #####
/home/nkanak/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:758: ConvergenceWarning: lbfgs failed to converge. Increase the number of iterations.
"of iterations.", ConvergenceWarning)
0.8555101184858971
(0.8555101184858971, 0.8555101184858971, 0.8555101184858971, None)
(0.7366250474523964, 0.7101390784071198, 0.7221328203055469, None)
(0.8526059243417644, 0.8555101184858971, 0.8533255868267997, None)
SVM ######
0.5286253538848694
(0.5286253538848694, 0.5286253538848694, 0.5286253538848694, None)
(0.639431552591954, 0.0740230525707726, 0.07954089224189759, None)
(0.5850924177735414, 0.5286253538848694, 0.3862355916847906, None)
k-NN #####
number of neighbors: 16
/home/nkanak/anaconda3/lib/python3.7/site-packages/sklearn/metrics/classification.py:1143: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.
'precision', 'predicted', average, warn_for)
0.6838628499528153
(0.6838628499528153, 0.6838628499528153, 0.6838628499528153, None)
(0.5191433476391912, 0.36735665672792295, 0.40104809150472626, None)
(0.6683744791096222, 0.6838628499528153, 0.6539392617656908, None)
k-NN sqrt #####
number of neighbors: 241
0.5965188214323163
(0.5965188214323163, 0.5965188214323163, 0.5965188214323163, None)
(0.6294695446636286, 0.1840539491307019, 0.2142795375206571, None)
(0.627329964559936, 0.5965188214323163, 0.5097257737375301, None)
Neural Network 1000 500 #####
0.8557722554262347
(0.8557722554262347, 0.8557722554262347, 0.8557722554262347, None)
(0.7447661116781966, 0.7056400952768699, 0.7207582477474749, None)
(0.8555949256254373, 0.8557722554262347, 0.8536172453327966, None)
Neural Network 2000 1000 #####
0.8592848904267589
(0.8592848904267589, 0.8592848904267589, 0.8592848904267589, None)
(0.7367248054957036, 0.7215161844133411, 0.7265455976192676, None)
(0.8576882482830546, 0.8592848904267589, 0.8573008253686647, None)