Measure

CfsSubsetEval_kNN1NKappa

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

Value per dataset

mbagrade (1)
wdbc (1) 0.87145344124174
vehicle (1) 0.57437055587854
jm1 (1) 0.11830560261068
cleveland (1)
ada_agnostic (1) 0.54821805884229
cholesterol (1)
madelon (1) 0.41538461538462
one-hundred-plants-texture (1) 0.40935283687943
micro-mass (2) 0.70142327238263
mfeat-zernike (1) 0.65111111111111
MagicTelescope (1) 0.59141417153215
mfeat-karhunen (1) 0.76611111111111
credit-a (1) 0.7101750574898
mushroom (1) 0.9738461616959
tamilnadu-electricity (1) 1
Click_prediction_small (5) 0.017862321654848
isolet (1) 0.79765560665029
cylinder-bands (2) 0.16417504756727
autoMpg (1)
mfeat-morphological (1) 0.67222222222222
pc1 (1) 0.10596240043855
credit-g (1) 0.30569684638861
qsar-biodeg (1) 0.57522129375546
iris-challenge (1) 0.88655862726406
spambase (1) 0.82088764456593
splice (1) 0.897812250821
anneal (3) 0.6191022730108
vowel (2) 0.66444444444444
ilpd (1) 0.14779196799508
blood-transfusion-service-center (1) 0.020630787037037
artificial-characters (1) 0.53453317466563
mozilla4 (1) 0.86663546475276
kc1 (1) 0.26043406740541
fourclass_scale (1)
analcatdata_dmft (1) 0.031950840204177
optdigits (1) 0.87128809286626
GesturePhaseSegmentationProcessed (1) 0.340256004749
eeg-eye-state (1) 0.5343988170413
wilt (1) 0.80464084286337
pharynx (1)
kin8nm (1)
gina_agnostic (1) 0.6994458764773
Amazon_employee_access (1) 0
sick (1) 0.77597197180175
profb (1) 0
wall-robot-navigation (1) 0.98147560504331
monks-problems-2 (1) 0
wisconsin (1)
triazines (1)
bolts (1)
har (1) 0.91252033200752
gas-drift (1) 0.93591052084793
scene (1) 0.73808363572709
mfeat-fourier (1) 0.71777777777778
anneal (2) 0.6191022730108
semeion (1) 0.66165532070498
one-hundred-plants-margin (1) 0.4084595959596
banknote-authentication (1) 0.84904975132881
cardiotocography (1) 1
cloud (1)
adult (2) 0.56362515511857
climate-model-simulation-crashes (1) 0.019180470793374
a (1) 0.9
letter (1) 0.84175686386753
Australian (3) 0.69117609802647
tic-tac-toe (1) 0.41922178864716
mfeat-pixel (1) 0.73611111111111
MiceProtein (1) 1
fruitfly (1)
analcatdata_authorship (1) 0.87859202217392
pc3 (1) 0
autoPrice (1)
auto_price (1)
musk (1) 0.99767132795188
hill-valley (1) 0
anneal (6) 0.6191022730108
ozone-level-8hr (1) 0.20297436483977
irish (1) 1
electricity (1) 0.49835333064918
satimage (1) 0.81678145242474
lowbwt (1)
nomao (1) 0.85744354977511
breast-w (1) 0.87687381157777
monks-problems-3 (1) 0.94940771277984
pbc (1)
delta_elevators (1)
vineyard (1)
texture (1) 0.9024
mfeat-factors (1) 0.85166666666667
eucalyptus (1) 0.46373071090787
pendigits (1) 0.9437860838946
pc4 (1) 0.30203725473562
UNIX_user_data (1)
detroit (1)
synthetic_control (1) 0.854
abalone (1) 0.10842616587071
anneal (5) 0.6191022730108
waveform-5000 (1) 0.64842460324626
LED-display-domain-7digit (1) 0.65302182403758
steel-plates-fault (1) 0.96800043334954
PhishingWebsites (1) 0.87226958364388
car (1) 0.7124332587407
a (2) 0.91
iris (2) 0.9
cpu_act (1)
anneal (7) 0.6191022730108
anneal (8) 0.6191022730108
anneal (11) 0.6191022730108
anneal (12) 0.81806507516465
anneal (9) 0.6191022730108
anneal (10) 0.6191022730108
anneal (13) 0.6191022730108
anneal (15) 0.81806507516465
TESTcd6b36175d-ModifiedWeather (1)
TEST79d5120512-XOR (1)
anneal (16) 0.6191022730108
TEST03ae3917f9-pandas_testing_dataset (1)
TESTfce9706bd8-pandas_testing_dataset (1)
anneal (20) 0.81806507516465
anneal (25) 0.6191022730108
anneal (64) 0.6191022730108
TESTc236f8668b-pandas_testing_dataset (1)
anneal (52) 0.6191022730108
anneal (23) 0.6191022730108
anneal (51) 0.6191022730108
TEST42f439d59e-ModifiedWeather (1)
TEST6cd383bd36-pandas_testing_dataset (3) -0.25
TESTb73fca9dea-pandas_testing_dataset (3) -0.25
TEST1c031057be-XOR (1)
anneal (69) 0.81806507516465
anneal (37) 0.6191022730108
anneal (28) 0.6191022730108
TEST68b8719aa6-pandas_testing_dataset (3) -0.25
anneal (54) 0.6191022730108
TEST497883d61c-XOR (1)
anneal (61) 0.6191022730108
anneal (77) 0.6191022730108
anneal (68) 0.6191022730108
TESTfb8c9dda6b-pandas_testing_dataset (1)
TEST12cee25e4e-ModifiedWeather (1)
TESTfb357f8e8d-ModifiedWeather (1)
TEST24233797e6-XOR (1)
TESTb1d41eaa75-XOR (1)
anneal (63) 0.6191022730108
TESTc236f8668b-pandas_testing_dataset (2)
anneal (21) 0.6191022730108
TEST63cf2e1fbd-pandas_testing_dataset (4)
anneal (58) 0.81806507516465
TESTfb8c9dda6b-pandas_testing_dataset (3)
anneal (76) 0.6191022730108
TEST2ea13bc990-pandas_testing_dataset (3) -0.25
anneal (18) 0.6191022730108
anneal (101) 0.6191022730108
anneal (47) 0.6191022730108
anneal (89) 0.6191022730108
anneal (14) 0.6191022730108
TEST0ce86503a9-XOR (1)
anneal (26) 0.81806507516465
anneal (45) 0.6191022730108
anneal (60) 0.6191022730108
anneal (39) 0.81806507516465
anneal (106) 0.6191022730108
anneal (86) 0.6191022730108
anneal (31) 0.6191022730108
anneal (78) 0.6191022730108
TEST843467ee18-XOR (1)
anneal (67) 0.6191022730108
TEST95346f9559-pandas_testing_dataset (3)
TEST15ca9f322a-pandas_testing_dataset (3) -0.25
anneal (100) 0.6191022730108
anneal (107) 0.6191022730108
TESTfd7b579d2e-UploadTestWithURL (1)
anneal (44) 0.6191022730108
anneal (22) 0.6191022730108
anneal (96) 0.6191022730108
anneal (84) 0.6191022730108
TEST03ae3917f9-pandas_testing_dataset (3) -0.25
TEST95346f9559-pandas_testing_dataset (2)
TEST2ea13bc990-pandas_testing_dataset (1)
TEST2ea13bc990-pandas_testing_dataset (2)
anneal (30) 0.6191022730108
TESTf376696645-ModifiedWeather (1)
anneal (34) 0.6191022730108
TEST6ca4501805-pandas_testing_dataset (1)
anneal (88) 0.6191022730108
anneal (36) 0.81806507516465
anneal (94) 0.6191022730108
anneal (72) 0.6191022730108
TESTe23b3943e2-XOR (1)
TESTc682124a7c-pandas_testing_dataset (3) -0.25
TEST15ca9f322a-pandas_testing_dataset (1)
TEST17559f05ba-XOR (1)
anneal (90) 0.6191022730108
TEST06a78f9b67-pandas_testing_dataset (2)
anneal (35) 0.81806507516465
anneal (41) 0.6191022730108
anneal (32) 0.6191022730108
TESTfb8c9dda6b-pandas_testing_dataset (2)
TEST6cd383bd36-pandas_testing_dataset (2)
TEST09797384d7-pandas_testing_dataset (2)
TESTfb8c9dda6b-pandas_testing_dataset (4)
TESTc236f8668b-pandas_testing_dataset (3)
TESTb73fca9dea-pandas_testing_dataset (2)
anneal (19) 0.6191022730108
TESTc31b13a56a-XOR (1)
anneal (75) 0.6191022730108
anneal (73) 0.6191022730108
anneal (55) 0.6191022730108
TESTe3a1b5909b-pandas_testing_dataset (1)
TEST15ca9f322a-pandas_testing_dataset (2)
TEST63cf2e1fbd-pandas_testing_dataset (2)
TEST09797384d7-pandas_testing_dataset (3)
TEST63cf2e1fbd-pandas_testing_dataset (1)
TEST95346f9559-pandas_testing_dataset (1)
TESTbd626c29c8-XOR (1)
anneal (95) 0.6191022730108
TEST06a78f9b67-pandas_testing_dataset (4)
anneal (33) 0.6191022730108
TEST95346f9559-pandas_testing_dataset (4)
anneal (59) 0.6191022730108
anneal (99) 0.6191022730108
anneal (82) 0.6191022730108
TEST6cd383bd36-pandas_testing_dataset (1)
TEST257d57cd52-XOR (1)
TEST09797384d7-pandas_testing_dataset (4)
TEST06a78f9b67-pandas_testing_dataset (3)
TESTad9ec77a46-UploadTestWithURL (1)
anneal (62) 0.6191022730108
TEST06a78f9b67-pandas_testing_dataset (1)
anneal (53) 0.6191022730108
anneal (93) 0.6191022730108
anneal (65) 0.81806507516465
anneal (38) 0.6191022730108
anneal (42) 0.6191022730108
anneal (66) 0.6191022730108
TEST09797384d7-pandas_testing_dataset (1)
TESTb73fca9dea-pandas_testing_dataset (1)
anneal (29) 0.6191022730108
anneal (24) 0.6191022730108
anneal (102) 0.81806507516465
anneal (97) 0.6191022730108
anneal (70) 0.84175686386753
TESTb3cf06a12a-ModifiedWeather (1)
TEST6ca4501805-pandas_testing_dataset (2)
TESTc236f8668b-pandas_testing_dataset (4)
TESTa7fbefc142-pandas_testing_dataset (2)
TEST63cf2e1fbd-pandas_testing_dataset (3)
TEST03ae3917f9-pandas_testing_dataset (2)
anneal (56) 0.81806507516465
anneal (103) 0.6191022730108
anneal (108) 0.94630150092687
anneal (109) 0.94630150092687
TEST6ca4501805-pandas_testing_dataset (3) -0.25
Bioresponse (1) 0.47447867397224
cjs (3) 1
dresses-sales (2) 0.057811928283937
pol (1)
sleep (1)
diabetes_numeric (1)
soybean (1) 0.85347528531452
JapaneseVowels (1) 0.83065140445486
first-order-theorem-proving (1) 0.3745241259497
one-hundred-plants-shape (1) 0.37815656565657
cmc (1) 0.23027588896024
cnae-9 (1) 0.78229166666667
segment (1) 0.9510101010101
monks-problems-1 (1) 0.49280575539568
sylva_agnostic (1) 0.91581149729292
bank-marketing (1) 0.42640597317081
phoneme (1) 0.55794303058604
anneal (115) 0.6191022730108
anneal (112) 0.94630150092687
quake (1)
collins (1) 1
kc2 (1) 0.33953660015288
diabetes (1) 0.38164732240097
kr-vs-kp (1) 0.88119202140591
balance-scale (1) 0.63739636554189
anneal (120) 0.6191022730108
anneal (122) 0.81806507516465
anneal (116) 0.6191022730108
anneal (129) 0.6191022730108
anneal (118) 0.6191022730108
anneal (111) 0.98879835542893
Weather (1) -0.13513513513514
anneal (124) 0.6191022730108
Weather (2) -0.13513513513514
anneal (126) 0.6191022730108
XOR (1)
anneal (119) 0.81806507516465
anneal (130) 0.6191022730108
anneal (125) 0.6191022730108
anneal (113) 0.6191022730108
anneal (121) 0.6191022730108
anneal (123) 0.94630150092687
Diabetes(scikit-learn) (1)
XOR (2)
anneal (117) 0.81806507516465
anneal (128) 0.6191022730108
anneal (132) 0.94630150092687
anneal (110) 0.94630150092687
anneal (131) 0.94630150092687
iris (1) 0.9
anneal (1) 0.6191022730108
longley (1)