Measure

kNN1NKappa

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

Value per dataset

credit-g (1) 0.30447470817121
pc1 (1) 0.40996301964622
first-order-theorem-proving (1) 0.38676358668194
hill-valley (1) 0.095709570957096
mushroom (1) 1
pc3 (1) 0.25757770674794
steel-plates-fault (1) 0.9864096884941
madelon (1) 0.085384615384615
phoneme (1) 0.68772270933328
vineyard (1)
isolet (1) 0.84994233772427
synthetic_control (1) 0.958
abalone (1) 0.10670901007122
mfeat-fourier (1) 0.765
mozilla4 (1) 0.72066084727756
cylinder-bands (2) 0.32113750650251
spambase (1) 0.77516774672954
banknote-authentication (1) 0.99704928468811
MiceProtein (1) 0.98622394913458
adult (2) 0.43096769138747
MagicTelescope (1) 0.5577522117348
pbc (1)
fourclass_scale (1)
mfeat-morphological (1) 0.63388888888889
bolts (1)
pharynx (1)
diabetes_numeric (1)
pendigits (1) 0.99120409421902
anneal (7) 0.82611029389283
semeion (1) 0.87233866454364
satimage (1) 0.86738379488485
vehicle (1) 0.57417298173988
GesturePhaseSegmentationProcessed (1) 0.47304121751664
wilt (1) 0.40351484770754
electricity (1) 0.54273634725232
breast-w (1) 0.90444466721955
musk (1) 0.9636889764997
anneal (6) 0.82611029389283
profb (1) -0.074626865671642
jm1 (1) 0.20020772020129
anneal (3) 0.82611029389283
anneal (17) 0.82611029389283
autoPrice (1)
cleveland (1)
cardiotocography (1) 1
scene (1) 0.74459481740215
ilpd (1) 0.17342046780926
mfeat-zernike (1) 0.77055555555556
wisconsin (1)
anneal (15) 0.82611029389283
anneal (22) 0.82611029389283
car (1) 0.7503139820421
cnae-9 (1) 0.7875
gina_agnostic (1) 0.62141353347369
kin8nm (1)
iris (2) 0.91
delta_elevators (1)
qsar-biodeg (1) 0.60872065925566
monks-problems-1 (1) 0.87410071942446
anneal (14) 0.82611029389283
texture (1) 0.9822
lowbwt (1)
anneal (2) 0.82611029389283
Australian (3) 0.64485337280825
eucalyptus (1) 0.40228622299671
one-hundred-plants-shape (1) 0.60037878787879
analcatdata_dmft (1) 0.034568250643874
anneal (34) 0.82611029389283
anneal (29) 0.82611029389283
anneal (23) 0.82611029389283
pol (1)
mbagrade (1)
Amazon_employee_access (1) 0.44261231987065
letter (1) 0.93983387821765
one-hundred-plants-texture (1) 0.75363390094867
TEST1c848ab209-pandas_testing_dataset (3) -0.25
PhishingWebsites (1) 0.92457141041463
detroit (1)
sylva_agnostic (1) 0.78651914116023
anneal (28) 0.82611029389283
anneal (53) 0.82611029389283
tamilnadu-electricity (1) 1
iris-challenge (1) 0.86132005509058
cholesterol (1)
anneal (41) 0.82611029389283
anneal (10) 0.82611029389283
anneal (35) 0.82611029389283
wdbc (1) 0.90520647994509
anneal (43) 0.82611029389283
anneal (60) 0.82611029389283
TESTebb33ef4fa-XOR (1)
anneal (44) 0.82611029389283
wall-robot-navigation (1) 0.79489275400317
anneal (25) 0.82611029389283
TEST29f9ae6987-XOR (1)
har (1) 0.94918957931045
Bioresponse (1) 0.45279151257497
artificial-characters (1) 0.76030669260697
anneal (51) 0.82611029389283
TEST0a3f20a3a8-pandas_testing_dataset (3) -0.25
anneal (37) 0.82611029389283
anneal (61) 0.82611029389283
anneal (8) 0.82611029389283
vowel (2) 0.91444444444444
nomao (1) 0.87252664303486
anneal (5) 0.82611029389283
anneal (87) 0.82611029389283
TESTc16ac7f367-pandas_testing_dataset (3)
anneal (62) 0.82611029389283
anneal (73) 0.82611029389283
anneal (65) 0.82611029389283
pc4 (1) 0.31895436040283
TEST861d5ffaea-XOR (1)
anneal (77) 0.82611029389283
anneal (59) 0.82611029389283
anneal (74) 0.82611029389283
gas-drift (1) 0.99284807277407
anneal (4) 0.82611029389283
LED-display-domain-7digit (1) 0.67074966741267
anneal (32) 0.82611029389283
anneal (9) 0.82611029389283
optdigits (1) 0.98121745508091
anneal (13) 0.82611029389283
mfeat-karhunen (1) 0.94444444444444
anneal (39) 0.82611029389283
anneal (55) 0.82611029389283
anneal (90) 0.82611029389283
JapaneseVowels (1) 0.9791905174141
anneal (38) 0.82611029389283
anneal (36) 0.82611029389283
anneal (71) 0.82611029389283
anneal (88) 0.82611029389283
anneal (19) 0.82611029389283
anneal (49) 0.82611029389283
anneal (93) 0.82611029389283
anneal (26) 0.82611029389283
anneal (72) 0.82611029389283
anneal (18) 0.82611029389283
anneal (33) 0.82611029389283
anneal (69) 0.82611029389283
anneal (56) 0.82611029389283
anneal (126) 0.82611029389283
sleep (1)
anneal (89) 0.82611029389283
anneal (42) 0.82611029389283
anneal (100) 0.82611029389283
monks-problems-2 (1) 0.26712518791414
anneal (115) 0.82611029389283
mfeat-factors (1) 0.95111111111111
anneal (91) 0.82611029389283
anneal (119) 0.82611029389283
TEST9103715299-pandas_testing_dataset (2)
sick (1) 0.61537854287767
anneal (111) 0.82611029389283
anneal (40) 0.82611029389283
anneal (132) 0.82611029389283
anneal (103) 0.82611029389283
anneal (133) 0.82611029389283
TEST1c3062c843-pandas_testing_dataset (3) -0.25
anneal (67) 0.82611029389283
anneal (95) 0.82611029389283
anneal (76) 0.82611029389283
anneal (144) 0.82611029389283
fruitfly (1)
anneal (16) 0.82611029389283
anneal (27) 0.82611029389283
TESTfab02098c0-pandas_testing_dataset (2)
splice (1) 0.59762629179099
anneal (147) 0.82611029389283
one-hundred-plants-margin (1) 0.71464646464646
anneal (80) 0.82611029389283
anneal (104) 0.82611029389283
TEST44eb4b8b3f-XOR (1)
anneal (97) 0.82611029389283
anneal (70) 0.82611029389283
anneal (125) 0.82611029389283
anneal (113) 0.82611029389283
ozone-level-8hr (1) 0.31421390253967
TESTb5b3545d7e-pandas_testing_dataset (3) -0.25
anneal (24) 0.82611029389283
TEST00a13efce9-pandas_testing_dataset (1)
triazines (1)
anneal (107) 0.82611029389283
anneal (173) 0.82611029389283
TESTfab02098c0-pandas_testing_dataset (3)
anneal (99) 0.82611029389283
anneal (176) 0.82611029389283
dresses-sales (2) 0.07762938230384
TESTa86b01f9a8-pandas_testing_dataset (3) -0.25
anneal (159) 0.82611029389283
anneal (158) 0.82611029389283
anneal (165) 0.82611029389283
TEST495d1e52d8-pandas_testing_dataset (1)
climate-model-simulation-crashes (1) 0.035184167124794
anneal (94) 0.82611029389283
anneal (146) 0.82611029389283
anneal (181) 0.82611029389283
anneal (178) 0.82611029389283
anneal (129) 0.82611029389283
anneal (131) 0.82611029389283
anneal (163) 0.82611029389283
TEST9b06efad03-pandas_testing_dataset (1)
TEST6abd679a4e-ModifiedWeather (1)
TEST388a9defc1-pandas_testing_dataset (4)
TEST84e16ea643-UploadTestWithURL (1)
mfeat-pixel (1) 0.94722222222222
anneal (105) 0.82611029389283
micro-mass (2) 0.57534005284274
anneal (148) 0.82611029389283
TESTd4a9ca9c2d-pandas_testing_dataset (3) -0.25
cmc (1) 0.14890873693558
TESTca4a634324-ModifiedWeather (1)
anneal (160) 0.82611029389283
anneal (136) 0.82611029389283
anneal (140) 0.82611029389283
anneal (121) 0.82611029389283
TEST5e105f0c38-pandas_testing_dataset (1)
anneal (164) 0.82611029389283
TEST78cf97e1d2-pandas_testing_dataset (3) -0.25
anneal (182) 0.82611029389283
TESTd746086797-XOR (1)
anneal (75) 0.82611029389283
anneal (112) 0.82611029389283
anneal (47) 0.82611029389283
anneal (153) 0.82611029389283
TEST9d1aa3a77e-XOR (1)
TEST495d1e52d8-pandas_testing_dataset (3) -0.25
TESTe3d8d93ab0-pandas_testing_dataset (3) -0.25
TEST0a395eb24e-XOR (1)
TEST5e105f0c38-pandas_testing_dataset (2)
cjs (3) 0.027477662164009
anneal (123) 0.82611029389283
TEST104676cb6a-pandas_testing_dataset (3)
anneal (201) 0.82611029389283
TEST2c4f0b6c26-pandas_testing_dataset (2)
anneal (155) 0.82611029389283
anneal (194) 0.82611029389283
anneal (167) 0.82611029389283
anneal (171) 0.82611029389283
anneal (162) 0.82611029389283
anneal (135) 0.82611029389283
anneal (223) 0.82611029389283
TESTdd0a5ebb6e-pandas_testing_dataset (2)
anneal (106) 0.82611029389283
TESTfab02098c0-pandas_testing_dataset (4)
anneal (161) 0.82611029389283
anneal (143) 0.82611029389283
anneal (197) 0.82611029389283
anneal (199) 0.82611029389283
anneal (137) 0.82611029389283
anneal (154) 0.82611029389283
anneal (134) 0.82611029389283
auto_price (1)
TEST104676cb6a-pandas_testing_dataset (4)
TESTd66c82a86b-ModifiedWeather (1)
TEST9b06efad03-pandas_testing_dataset (2)
kc1 (1) 0.35045478814046
anneal (228) 0.82611029389283
TEST0be3452fe0-pandas_testing_dataset (2)
anneal (212) 0.82611029389283
anneal (204) 0.82611029389283
anneal (79) 0.82611029389283
anneal (145) 0.82611029389283
anneal (229) 0.82611029389283
TESTdd0a5ebb6e-pandas_testing_dataset (1)
TEST388a9defc1-pandas_testing_dataset (2)
TEST104676cb6a-pandas_testing_dataset (1)
anneal (218) 0.82611029389283
TESTdd0a5ebb6e-pandas_testing_dataset (3)
anneal (198) 0.82611029389283
TEST0be3452fe0-pandas_testing_dataset (3) -0.25
anneal (98) 0.82611029389283
anneal (12) 0.82611029389283
anneal (214) 0.82611029389283
anneal (120) 0.82611029389283
anneal (209) 0.82611029389283
anneal (256) 0.82611029389283
anneal (110) 0.82611029389283
segment (1) 0.94343434343434
tic-tac-toe (1) 0.93674278922578
anneal (157) 0.82611029389283
TEST5e105f0c38-pandas_testing_dataset (3) -0.25
anneal (102) 0.82611029389283
anneal (262) 0.82611029389283
anneal (170) 0.82611029389283
TEST6ba4d7daec-XOR (1)
anneal (232) 0.82611029389283
anneal (237) 0.82611029389283
anneal (241) 0.82611029389283
anneal (221) 0.82611029389283
TESTc8f1eae46a-XOR (1)
TEST44aee7d221-ModifiedWeather (1)
TEST495d1e52d8-pandas_testing_dataset (2)
TEST2c4f0b6c26-pandas_testing_dataset (1)
autoMpg (1)
anneal (193) 0.82611029389283
anneal (219) 0.82611029389283
TEST2c4f0b6c26-pandas_testing_dataset (3) -0.25
TEST9103715299-pandas_testing_dataset (3) -0.25
anneal (208) 0.82611029389283
anneal (255) 0.82611029389283
anneal (203) 0.82611029389283
anneal (253) 0.82611029389283
anneal (270) 0.82611029389283
anneal (63) 0.82611029389283
anneal (210) 0.82611029389283
TEST388a9defc1-pandas_testing_dataset (3)
anneal (268) 0.82611029389283
anneal (271) 0.82611029389283
TESTe74389f4b6-XOR (1)
anneal (222) 0.82611029389283
anneal (195) 0.82611029389283
anneal (250) 0.82611029389283
anneal (205) 0.82611029389283
anneal (128) 0.82611029389283
anneal (233) 0.82611029389283
anneal (82) 0.82611029389283
TESTf738f069ca-pandas_testing_dataset (4)
anneal (225) 0.82611029389283
TESTdd0a5ebb6e-pandas_testing_dataset (4)
anneal (184) 0.82611029389283
anneal (68) 0.82611029389283
anneal (236) 0.82611029389283
anneal (186) 0.82611029389283
anneal (191) 0.82611029389283
anneal (166) 0.82611029389283
anneal (247) 0.82611029389283
anneal (248) 0.82611029389283
anneal (269) 0.82611029389283
anneal (11) 0.82611029389283
anneal (92) 0.82611029389283
anneal (267) 0.82611029389283
anneal (226) 0.82611029389283
anneal (257) 0.82611029389283
anneal (190) 0.82611029389283
anneal (263) 0.82611029389283
TESTdd2273bbad-pandas_testing_dataset (3) -0.25
TESTbdcda46197-pandas_testing_dataset (3) -0.25
quake (1)
TESTcbac53b2c5-XOR (1)
anneal (57) 0.82611029389283
TESTb7d5691345-XOR (1)
anneal (192) 0.82611029389283
anneal (230) 0.82611029389283
anneal (202) 0.82611029389283
anneal (251) 0.82611029389283
anneal (206) 0.82611029389283
anneal (139) 0.82611029389283
anneal (188) 0.82611029389283
TEST5037c378b1-pandas_testing_dataset (3) -0.25
TEST388a9defc1-pandas_testing_dataset (1)
anneal (152) 0.82611029389283
TEST9b06efad03-pandas_testing_dataset (3) -0.25
anneal (266) 0.82611029389283
anneal (187) 0.82611029389283
anneal (200) 0.82611029389283
anneal (254) 0.82611029389283
anneal (242) 0.82611029389283
anneal (240) 0.82611029389283
anneal (213) 0.82611029389283
anneal (183) 0.82611029389283
Click_prediction_small (5) 0.066527078552399
anneal (156) 0.82611029389283
TEST2f9e899c65-XOR (1)
anneal (246) 0.82611029389283
anneal (151) 0.82611029389283
anneal (52) 0.82611029389283
anneal (109) 0.82611029389283
anneal (215) 0.82611029389283
anneal (261) 0.82611029389283
anneal (168) 0.82611029389283
TEST3620d8fbd0-XOR (1)
anneal (258) 0.82611029389283
irish (1) 0.95562225664859
anneal (239) 0.82611029389283
anneal (252) 0.82611029389283
anneal (81) 0.82611029389283
anneal (244) 0.82611029389283
TEST104676cb6a-pandas_testing_dataset (2)
TESTc16ac7f367-pandas_testing_dataset (4)
TESTfab02098c0-pandas_testing_dataset (1)
anneal (275) 0.82611029389283
anneal (274) 0.82611029389283
anneal (312) 0.82611029389283
anneal (280) 0.82611029389283
anneal (286) 0.82611029389283
anneal (301) 0.82611029389283
anneal (282) 0.82611029389283
anneal (284) 0.82611029389283
anneal (273) 0.82611029389283
anneal (278) 0.82611029389283
anneal (333) 0.82611029389283
anneal (318) 0.82611029389283
anneal (359) 0.82611029389283
anneal (356) 0.82611029389283
anneal (385) 0.82611029389283
anneal (379) 0.82611029389283
anneal (298) 0.82611029389283
anneal (311) 0.82611029389283
anneal (320) 0.82611029389283
anneal (362) 0.82611029389283
anneal (355) 0.82611029389283
anneal (357) 0.82611029389283
anneal (337) 0.82611029389283
anneal (381) 0.82611029389283
anneal (335) 0.82611029389283
anneal (336) 0.82611029389283
anneal (384) 0.82611029389283
TESTfa348335d3-pandas_testing_dataset (3) -0.25
anneal (332) 0.82611029389283
anneal (346) 0.82611029389283
anneal (388) 0.82611029389283
anneal (305) 0.82611029389283
anneal (343) 0.82611029389283
anneal (288) 0.82611029389283
TEST845a642017-pandas_testing_dataset (3) -0.25
anneal (340) 0.82611029389283
anneal (374) 0.82611029389283
anneal (372) 0.82611029389283
anneal (371) 0.82611029389283
TEST5b30e679ed-pandas_testing_dataset (1)
anneal (383) 0.82611029389283
anneal (358) 0.82611029389283
anneal (395) 0.82611029389283
TEST6f97db9a3e-ModifiedWeather (1)
anneal (290) 0.82611029389283
anneal (324) 0.82611029389283
TEST5b30e679ed-pandas_testing_dataset (4)
TEST7dc1ecdb15-XOR (1)
anneal (354) 0.82611029389283
anneal (303) 0.82611029389283
anneal (319) 0.82611029389283
anneal (334) 0.82611029389283
anneal (405) 0.82611029389283
anneal (404) 0.82611029389283
anneal (308) 0.82611029389283
anneal (398) 0.82611029389283
anneal (291) 0.82611029389283
TEST6dc49fc872-pandas_testing_dataset (2)
anneal (402) 0.82611029389283
TESTb410f44fd0-pandas_testing_dataset (3)
anneal (317) 0.82611029389283
TESTb410f44fd0-pandas_testing_dataset (1)
TESTc5c73d43cf-XOR (1)
anneal (360) 0.82611029389283
anneal (403) 0.82611029389283
anneal (277) 0.82611029389283
anneal (407) 0.82611029389283
TEST5b30e679ed-pandas_testing_dataset (3)
anneal (410) 0.82611029389283
anneal (361) 0.82611029389283
TEST9161e0d711-pandas_testing_dataset (3) -0.25
TESTeedf1c617e-pandas_testing_dataset (3)
TEST58188dfbc6-pandas_testing_dataset (3)
TESTa5e33d6c29-pandas_testing_dataset (1)
TESTb410f44fd0-pandas_testing_dataset (2)
TEST6dc49fc872-pandas_testing_dataset (1)
TESTb918af0e2d-pandas_testing_dataset (4)
anneal (409) 0.82611029389283
anneal (347) 0.82611029389283
anneal (295) 0.82611029389283
anneal (348) 0.82611029389283
TEST0938a9daba-pandas_testing_dataset (3) -0.25
anneal (287) 0.82611029389283
TESTca5628eaef-pandas_testing_dataset (1)
anneal (314) 0.82611029389283
anneal (408) 0.82611029389283
TESTc9ed3920cd-XOR (1)
TESTeedf1c617e-pandas_testing_dataset (2)
TESTa5e33d6c29-pandas_testing_dataset (3) -0.25
TESTa10ede6728-XOR (1)
anneal (342) 0.82611029389283
TESTeedf1c617e-pandas_testing_dataset (4)
TESTb918af0e2d-pandas_testing_dataset (3)
anneal (422) 0.82611029389283
anneal (296) 0.82611029389283
anneal (276) 0.82611029389283
anneal (418) 0.82611029389283
anneal (304) 0.82611029389283
anneal (399) 0.82611029389283
TESTa5e33d6c29-pandas_testing_dataset (2)
anneal (390) 0.82611029389283
TEST10c25a3b38-pandas_testing_dataset (3) -0.25
anneal (424) 0.82611029389283
TESTed776f0840-pandas_testing_dataset (3) -0.25
anneal (412) 0.82611029389283
anneal (417) 0.82611029389283
anneal (283) 0.82611029389283
anneal (425) 0.82611029389283
anneal (400) 0.82611029389283
TESTed7333f3d2-ModifiedWeather (1)
anneal (420) 0.82611029389283
anneal (413) 0.82611029389283
anneal (423) 0.82611029389283
TESTf9ea71bde7-XOR (1)
anneal (325) 0.82611029389283
TEST5b30e679ed-pandas_testing_dataset (2)
anneal (434) 0.82611029389283
anneal (365) 0.82611029389283
anneal (426) 0.82611029389283
TEST855da0f4bb-ModifiedWeather (1)
TEST84e82f2c56-ModifiedWeather (1)
TESTb9093fb3b4-ModifiedWeather (1)
TEST178704e3b7-ModifiedWeather (1)
anneal (393) 0.82611029389283
TESTd655778eb6-ModifiedWeather (1)
anneal (438) 0.82611029389283
TEST17eccd9837-pandas_testing_dataset (3)
anneal (433) 0.82611029389283
TESTb918af0e2d-pandas_testing_dataset (2)
TESTca5628eaef-pandas_testing_dataset (2)
TESTf2a16c917e-XOR (1)
anneal (429) 0.82611029389283
anneal (443) 0.82611029389283
anneal (401) 0.82611029389283
anneal (363) 0.82611029389283
anneal (344) 0.82611029389283
anneal (380) 0.82611029389283
TEST6dc49fc872-pandas_testing_dataset (3) -0.25