[Creating the subsets for the values]
[Creating the subsets for the labels "1"-"0"]
[Optimization of the hyper-parameter k start]
[Training the kNN model (with k=1) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6264594
Area under curve (Davis & Goadrich):
0.6264609
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6028206 (worst possible: -1; best possible: +1)
When k=1, the MCC value is 0.6028206 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=2) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6169076
Area under curve (Davis & Goadrich):
0.616909
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.5923581 (worst possible: -1; best possible: +1)
When k=2, the MCC value is 0.5923581 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=3) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6830796
Area under curve (Davis & Goadrich):
0.6830816
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6636884 (worst possible: -1; best possible: +1)
When k=3, the MCC value is 0.6636884 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=4) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6616313
Area under curve (Davis & Goadrich):
0.661633
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6385756 (worst possible: -1; best possible: +1)
When k=4, the MCC value is 0.6385756 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=5) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6620504
Area under curve (Davis & Goadrich):
0.6620522
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6413557 (worst possible: -1; best possible: +1)
When k=5, the MCC value is 0.6413557 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=6) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6755082
Area under curve (Davis & Goadrich):
0.6755101
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6569899 (worst possible: -1; best possible: +1)
When k=6, the MCC value is 0.6569899 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=7) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6837836
Area under curve (Davis & Goadrich):
0.6837855
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6655734 (worst possible: -1; best possible: +1)
When k=7, the MCC value is 0.6655734 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=8) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6800778
Area under curve (Davis & Goadrich):
0.6800797
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6621069 (worst possible: -1; best possible: +1)
When k=8, the MCC value is 0.6621069 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=9) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6723174
Area under curve (Davis & Goadrich):
0.6723192
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6527535 (worst possible: -1; best possible: +1)
When k=9, the MCC value is 0.6527535 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=10) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6811248
Area under curve (Davis & Goadrich):
0.6811267
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.660644 (worst possible: -1; best possible: +1)
When k=10, the MCC value is 0.660644 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=11) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6818313
Area under curve (Davis & Goadrich):
0.6818332
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6625213 (worst possible: -1; best possible: +1)
When k=11, the MCC value is 0.6625213 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=12) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6823706
Area under curve (Davis & Goadrich):
0.6823725
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6646654 (worst possible: -1; best possible: +1)
When k=12, the MCC value is 0.6646654 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=13) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6832644
Area under curve (Davis & Goadrich):
0.6832663
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6634545 (worst possible: -1; best possible: +1)
When k=13, the MCC value is 0.6634545 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=14) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.677557
Area under curve (Davis & Goadrich):
0.6775589
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6568918 (worst possible: -1; best possible: +1)
When k=14, the MCC value is 0.6568918 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=15) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6834522
Area under curve (Davis & Goadrich):
0.6834542
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6632248 (worst possible: -1; best possible: +1)
When k=15, the MCC value is 0.6632248 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=16) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6765703
Area under curve (Davis & Goadrich):
0.6765722
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6584004 (worst possible: -1; best possible: +1)
When k=16, the MCC value is 0.6584004 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=17) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6905335
Area under curve (Davis & Goadrich):
0.6905355
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6735008 (worst possible: -1; best possible: +1)
When k=17, the MCC value is 0.6735008 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=18) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.687534
Area under curve (Davis & Goadrich):
0.687536
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6690656 (worst possible: -1; best possible: +1)
When k=18, the MCC value is 0.6690656 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=19) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6841468
Area under curve (Davis & Goadrich):
0.6841488
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6650927 (worst possible: -1; best possible: +1)
When k=19, the MCC value is 0.6650927 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=20) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6793496
Area under curve (Davis & Goadrich):
0.6793515
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6601956 (worst possible: -1; best possible: +1)
When k=20, the MCC value is 0.6601956 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=21) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.680415
Area under curve (Davis & Goadrich):
0.6804169
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6616029 (worst possible: -1; best possible: +1)
When k=21, the MCC value is 0.6616029 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=22) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6828979
Area under curve (Davis & Goadrich):
0.6828998
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6639265 (worst possible: -1; best possible: +1)
When k=22, the MCC value is 0.6639265 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=23) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6859101
Area under curve (Davis & Goadrich):
0.6859121
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6683802 (worst possible: -1; best possible: +1)
When k=23, the MCC value is 0.6683802 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=24) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6790152
Area under curve (Davis & Goadrich):
0.6790171
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6606992 (worst possible: -1; best possible: +1)
When k=24, the MCC value is 0.6606992 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=25) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6823706
Area under curve (Davis & Goadrich):
0.6823725
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6646654 (worst possible: -1; best possible: +1)
When k=25, the MCC value is 0.6646654 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=26) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6814796
Area under curve (Davis & Goadrich):
0.6814815
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6630094 (worst possible: -1; best possible: +1)
When k=26, the MCC value is 0.6630094 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=27) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6793496
Area under curve (Davis & Goadrich):
0.6793515
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6601956 (worst possible: -1; best possible: +1)
When k=27, the MCC value is 0.6601956 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=28) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6770507
Area under curve (Davis & Goadrich):
0.6770526
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.657628 (worst possible: -1; best possible: +1)
When k=28, the MCC value is 0.657628 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=29) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6807639
Area under curve (Davis & Goadrich):
0.6807658
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6611152 (worst possible: -1; best possible: +1)
When k=29, the MCC value is 0.6611152 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=30) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6732314
Area under curve (Davis & Goadrich):
0.6732333
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6544314 (worst possible: -1; best possible: +1)
When k=30, the MCC value is 0.6544314 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=31) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6700402
Area under curve (Davis & Goadrich):
0.6700421
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6501895 (worst possible: -1; best possible: +1)
When k=31, the MCC value is 0.6501895 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=32) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6700402
Area under curve (Davis & Goadrich):
0.6700421
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6501895 (worst possible: -1; best possible: +1)
When k=32, the MCC value is 0.6501895 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=33) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6755082
Area under curve (Davis & Goadrich):
0.6755101
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6569899 (worst possible: -1; best possible: +1)
When k=33, the MCC value is 0.6569899 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=34) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6781162
Area under curve (Davis & Goadrich):
0.6781181
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6590371 (worst possible: -1; best possible: +1)
When k=34, the MCC value is 0.6590371 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=35) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6688331
Area under curve (Davis & Goadrich):
0.6688349
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6490422 (worst possible: -1; best possible: +1)
When k=35, the MCC value is 0.6490422 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=36) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6680522
Area under curve (Davis & Goadrich):
0.668054
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.647093 (worst possible: -1; best possible: +1)
When k=36, the MCC value is 0.647093 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=37) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6706786
Area under curve (Davis & Goadrich):
0.6706804
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6524217 (worst possible: -1; best possible: +1)
When k=37, the MCC value is 0.6524217 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=38) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6685574
Area under curve (Davis & Goadrich):
0.6685592
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6495905 (worst possible: -1; best possible: +1)
When k=38, the MCC value is 0.6495905 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=39) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6672332
Area under curve (Davis & Goadrich):
0.667235
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.648737 (worst possible: -1; best possible: +1)
When k=39, the MCC value is 0.648737 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=40) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6684234
Area under curve (Davis & Goadrich):
0.6684253
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6498704 (worst possible: -1; best possible: +1)
When k=40, the MCC value is 0.6498704 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=41) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6681633
Area under curve (Davis & Goadrich):
0.6681652
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6504415 (worst possible: -1; best possible: +1)
When k=41, the MCC value is 0.6504415 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=42) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6604042
Area under curve (Davis & Goadrich):
0.660406
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6413865 (worst possible: -1; best possible: +1)
When k=42, the MCC value is 0.6413865 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=43) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6613514
Area under curve (Davis & Goadrich):
0.6613532
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6431107 (worst possible: -1; best possible: +1)
When k=43, the MCC value is 0.6431107 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=44) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6615746
Area under curve (Davis & Goadrich):
0.6615763
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6425109 (worst possible: -1; best possible: +1)
When k=44, the MCC value is 0.6425109 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=45) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6605155
Area under curve (Davis & Goadrich):
0.6605173
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6410885 (worst possible: -1; best possible: +1)
When k=45, the MCC value is 0.6410885 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=46) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6648667
Area under curve (Davis & Goadrich):
0.6648685
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6464784 (worst possible: -1; best possible: +1)
When k=46, the MCC value is 0.6464784 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=47) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6628686
Area under curve (Davis & Goadrich):
0.6628704
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6433473 (worst possible: -1; best possible: +1)
When k=47, the MCC value is 0.6433473 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=48) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6593459
Area under curve (Davis & Goadrich):
0.6593476
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6399632 (worst possible: -1; best possible: +1)
When k=48, the MCC value is 0.6399632 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=49) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6615746
Area under curve (Davis & Goadrich):
0.6615763
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6425109 (worst possible: -1; best possible: +1)
When k=49, the MCC value is 0.6425109 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=50) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6629903
Area under curve (Davis & Goadrich):
0.6629921
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6430603 (worst possible: -1; best possible: +1)
When k=50, the MCC value is 0.6430603 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=51) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6571225
Area under curve (Davis & Goadrich):
0.6571242
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6374154 (worst possible: -1; best possible: +1)
When k=51, the MCC value is 0.6374154 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=52) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6571225
Area under curve (Davis & Goadrich):
0.6571242
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6374154 (worst possible: -1; best possible: +1)
When k=52, the MCC value is 0.6374154 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=53) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6571225
Area under curve (Davis & Goadrich):
0.6571242
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6374154 (worst possible: -1; best possible: +1)
When k=53, the MCC value is 0.6374154 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=54) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6550037
Area under curve (Davis & Goadrich):
0.6550054
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6345626 (worst possible: -1; best possible: +1)
When k=54, the MCC value is 0.6345626 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=55) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6559627
Area under curve (Davis & Goadrich):
0.6559644
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6362946 (worst possible: -1; best possible: +1)
When k=55, the MCC value is 0.6362946 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=56) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.65453
Area under curve (Davis & Goadrich):
0.6545317
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6361237 (worst possible: -1; best possible: +1)
When k=56, the MCC value is 0.6361237 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=57) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.65778
Area under curve (Davis & Goadrich):
0.6577817
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6400827 (worst possible: -1; best possible: +1)
When k=57, the MCC value is 0.6400827 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=58) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6537498
Area under curve (Davis & Goadrich):
0.6537515
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6337486 (worst possible: -1; best possible: +1)
When k=58, the MCC value is 0.6337486 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=59) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6591333
Area under curve (Davis & Goadrich):
0.659135
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.64057 (worst possible: -1; best possible: +1)
When k=59, the MCC value is 0.64057 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=60) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6525102
Area under curve (Davis & Goadrich):
0.6525119
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6329479 (worst possible: -1; best possible: +1)
When k=60, the MCC value is 0.6329479 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=61) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6534768
Area under curve (Davis & Goadrich):
0.6534785
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6346958 (worst possible: -1; best possible: +1)
When k=61, the MCC value is 0.6346958 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=62) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6500728
Area under curve (Davis & Goadrich):
0.6500745
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6313858 (worst possible: -1; best possible: +1)
When k=62, the MCC value is 0.6313858 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=63) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6534768
Area under curve (Davis & Goadrich):
0.6534785
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6346958 (worst possible: -1; best possible: +1)
When k=63, the MCC value is 0.6346958 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=64) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6570203
Area under curve (Davis & Goadrich):
0.657022
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6377206 (worst possible: -1; best possible: +1)
When k=64, the MCC value is 0.6377206 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=65) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6533903
Area under curve (Davis & Goadrich):
0.653392
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6350186 (worst possible: -1; best possible: +1)
When k=65, the MCC value is 0.6350186 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=66) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6501507
Area under curve (Davis & Goadrich):
0.6501524
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6310562 (worst possible: -1; best possible: +1)
When k=66, the MCC value is 0.6310562 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=67) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6425675
Area under curve (Davis & Goadrich):
0.6425691
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6220184 (worst possible: -1; best possible: +1)
When k=67, the MCC value is 0.6220184 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=68) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6481208
Area under curve (Davis & Goadrich):
0.6481225
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6278665 (worst possible: -1; best possible: +1)
When k=68, the MCC value is 0.6278665 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=69) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6436853
Area under curve (Davis & Goadrich):
0.643687
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6231183 (worst possible: -1; best possible: +1)
When k=69, the MCC value is 0.6231183 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=70) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6535655
Area under curve (Davis & Goadrich):
0.6535673
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6343766 (worst possible: -1; best possible: +1)
When k=70, the MCC value is 0.6343766 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=71) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6524229
Area under curve (Davis & Goadrich):
0.6524246
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6332672 (worst possible: -1; best possible: +1)
When k=71, the MCC value is 0.6332672 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=72) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6514541
Area under curve (Davis & Goadrich):
0.6514558
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6315184 (worst possible: -1; best possible: +1)
When k=72, the MCC value is 0.6315184 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=73) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6491761
Area under curve (Davis & Goadrich):
0.6491778
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6292987 (worst possible: -1; best possible: +1)
When k=73, the MCC value is 0.6292987 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=74) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6493398
Area under curve (Davis & Goadrich):
0.6493415
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6286567 (worst possible: -1; best possible: +1)
When k=74, the MCC value is 0.6286567 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=75) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.645934
Area under curve (Davis & Goadrich):
0.6459356
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6253258 (worst possible: -1; best possible: +1)
When k=75, the MCC value is 0.6253258 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=76) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6492569
Area under curve (Davis & Goadrich):
0.6492585
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6289759 (worst possible: -1; best possible: +1)
When k=76, the MCC value is 0.6289759 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=77) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6516325
Area under curve (Davis & Goadrich):
0.6516342
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6308905 (worst possible: -1; best possible: +1)
When k=77, the MCC value is 0.6308905 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=78) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6504839
Area under curve (Davis & Goadrich):
0.6504856
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6297723 (worst possible: -1; best possible: +1)
When k=78, the MCC value is 0.6297723 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=79) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6481208
Area under curve (Davis & Goadrich):
0.6481225
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6278665 (worst possible: -1; best possible: +1)
When k=79, the MCC value is 0.6278665 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=80) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6438215
Area under curve (Davis & Goadrich):
0.6438231
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6224554 (worst possible: -1; best possible: +1)
When k=80, the MCC value is 0.6224554 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=81) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6460845
Area under curve (Davis & Goadrich):
0.6460862
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6246768 (worst possible: -1; best possible: +1)
When k=81, the MCC value is 0.6246768 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=82) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6450257
Area under curve (Davis & Goadrich):
0.6450273
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6232419 (worst possible: -1; best possible: +1)
When k=82, the MCC value is 0.6232419 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=83) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6405828
Area under curve (Davis & Goadrich):
0.6405844
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6184729 (worst possible: -1; best possible: +1)
When k=83, the MCC value is 0.6184729 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=84) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.64164
Area under curve (Davis & Goadrich):
0.6416416
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6199112 (worst possible: -1; best possible: +1)
When k=84, the MCC value is 0.6199112 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=85) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.64164
Area under curve (Davis & Goadrich):
0.6416416
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6199112 (worst possible: -1; best possible: +1)
When k=85, the MCC value is 0.6199112 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=86) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6404597
Area under curve (Davis & Goadrich):
0.6404613
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6191429 (worst possible: -1; best possible: +1)
When k=86, the MCC value is 0.6191429 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=87) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6372388
Area under curve (Davis & Goadrich):
0.6372403
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6151631 (worst possible: -1; best possible: +1)
When k=87, the MCC value is 0.6151631 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=88) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6381885
Area under curve (Davis & Goadrich):
0.6381901
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6172943 (worst possible: -1; best possible: +1)
When k=88, the MCC value is 0.6172943 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=89) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6384067
Area under curve (Davis & Goadrich):
0.6384083
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6159269 (worst possible: -1; best possible: +1)
When k=89, the MCC value is 0.6159269 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=90) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6395249
Area under curve (Davis & Goadrich):
0.6395265
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6170336 (worst possible: -1; best possible: +1)
When k=90, the MCC value is 0.6170336 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=91) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6438927
Area under curve (Davis & Goadrich):
0.6438943
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6221291 (worst possible: -1; best possible: +1)
When k=91, the MCC value is 0.6221291 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=92) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6428339
Area under curve (Davis & Goadrich):
0.6428355
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6206924 (worst possible: -1; best possible: +1)
When k=92, the MCC value is 0.6206924 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=93) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6438927
Area under curve (Davis & Goadrich):
0.6438943
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6221291 (worst possible: -1; best possible: +1)
When k=93, the MCC value is 0.6221291 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=94) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6394047
Area under curve (Davis & Goadrich):
0.6394063
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6177038 (worst possible: -1; best possible: +1)
When k=94, the MCC value is 0.6177038 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=95) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6415759
Area under curve (Davis & Goadrich):
0.6415776
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6202445 (worst possible: -1; best possible: +1)
When k=95, the MCC value is 0.6202445 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=96) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6438215
Area under curve (Davis & Goadrich):
0.6438231
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6224554 (worst possible: -1; best possible: +1)
When k=96, the MCC value is 0.6224554 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=97) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6406475
Area under curve (Davis & Goadrich):
0.6406491
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6181429 (worst possible: -1; best possible: +1)
When k=97, the MCC value is 0.6181429 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=98) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.638528
Area under curve (Davis & Goadrich):
0.6385296
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6152634 (worst possible: -1; best possible: +1)
When k=98, the MCC value is 0.6152634 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=99) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.6405828
Area under curve (Davis & Goadrich):
0.6405844
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6184729 (worst possible: -1; best possible: +1)
When k=99, the MCC value is 0.6184729 (worst possible: -1; best possible: +1)
[Training the kNN model (with k=100) on training set & applying the kNN model to validation set]
Precision-recall curve
Area under curve (Integral):
0.642631
Area under curve (Davis & Goadrich):
0.6426326
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6216818 (worst possible: -1; best possible: +1)
When k=100, the MCC value is 0.6216818 (worst possible: -1; best possible: +1)
The best k value is 17, corresponding to MCC=0.673500820316828
[Optimization end]
[Training the kNN model (with the OPTIMIZED hyper-parameter k=17) on training set & applying the kNN to the test set]
Precision-recall curve
Area under curve (Integral):
0.6743471
Area under curve (Davis & Goadrich):
0.674349
Curve not computed ( can be done by using curve=TRUE )
MCC = 0.6472466 (worst possible: -1; best possible: +1)
f1_score = 0.7272727 (worst: 0.0; best: 1.0)
accuracy = 0.8678794 (worst: 0.0; best: 1.0)
true positive rate = recall = 0.6594982 (worst: 0.0; best: 1.0)
true negative rate = specificity = 0.9438276 (worst: 0.0; best: 1.0)
Datasets
Models
