Measure

AutoCorrelation

Average class difference between consecutive instances.

Value per dataset

triazines (1) 0.83311891891892
anneal (8) 0.60646599777035
anneal (4) 0.60646599777035
anneal (2) 0.60646599777035
XOR (1) 0.33333333333333
Weather (1) 0.53846153846154
web_questionsQA (1) 1
anneal (6) 0.60646599777035
anneal (7) 0.60646599777035
Weather (2) 0.53846153846154
TEST381a3dd20c-NumPy_testing_dataset (1) 0
TEST9e3886e694-XOR (1) 0.33333333333333
iris (2) 0.98657718120805
anneal (12) 0.60646599777035
anneal (14) 0.040902045102255
TESTc7ba0dcb5a-XOR (1) 0.33333333333333
TESTed4a84a4bb-pandas_testing_dataset (2) 0.33333333333333
test (6) 0.98657718120805
TEST51ef687b9d-pandas_testing_dataset (2) 0
Diabetes(scikit-learn) (1) -84.637188208617
anneal (13) 0.60646599777035
TESTb633b550cf-pandas_testing_dataset (1) 0.75
test (4) 0.98657718120805
TEST51ef687b9d-pandas_testing_dataset (1) 0
TESTed4a84a4bb-pandas_testing_dataset (1) 0.75
test (3) 0.98657718120805
test (1) 0.98657718120805
test (2) 0.98657718120805
TEST51ef687b9d-pandas_testing_dataset (4) 0
anneal (9) 0.49386845039019
TESTaf99b42041-ModifiedWeather (1) 0.53846153846154
XOR (2) 0.33333333333333
test (9) 0.98657718120805
anneal (17) 0.60646599777035
test (7) 0.98657718120805
TESTe216022baf-UploadTestWithURL (1)
iris-challenge (1) 0.77852348993289
TEST8facacd8dc-UploadTestWithURL (1)
test (10) 0.98657718120805
test (14) 0.98657718120805
test (5) 0.98657718120805
test (13) 0.98657718120805
test (12) 0.98657718120805
TEST51ef687b9d-pandas_testing_dataset (3) 0
TESTed4a84a4bb-pandas_testing_dataset (3) 0
anneal (3) 0.60646599777035
anneal (23) 0.60646599777035
TEST0ea351d931-pandas_testing_dataset (1) 0
anneal (24) 0.60646599777035
anneal (18) 0.60646599777035
test (11) 0.98657718120805
test (8) 0.98657718120805
cpu_act (1) -14.015504822366
anneal (26) 0.60646599777035
anneal (27) 0.60646599777035
anneal (39) 0.60646599777035
anneal (43) 0.60646599777035
anneal (63) 0.60646599777035
test (16) 0.98657718120805
TEST840571e677-pandas_testing_dataset (1) 0.75
anneal (58) 0.60646599777035
Weather (6) 0.53846153846154
anneal (62) 0.60646599777035
anneal (30) 0.60646599777035
test (24) 0.98657718120805
test (20) 0.98657718120805
anneal (66) 0.49386845039019
anneal (34) 0.60646599777035
anneal (38) 0.60646599777035
anneal (41) 0.60646599777035
Weather (3) 0.53846153846154
XOR (4) 0.33333333333333
Weather (4) 0.53846153846154
Weather (8) 0.53846153846154
test (19) 0.98657718120805
test (21) 0.98657718120805
Diabetes(scikit-learn) (3) -84.637188208617
XOR (3) 0.33333333333333
anneal (48) 0.60646599777035
XOR (6) 0.33333333333333
test (27) 0.98657718120805
XOR (5) 0.33333333333333
bolts (1) -13.571282051282
spambase (1) 0.99978260869565
anneal (49) 0.60646599777035
test (33) 0.98657718120805
anneal (32) 0.60646599777035
anneal (45) 0.60646599777035
anneal (16) 0.60646599777035
anneal (57) 0.60646599777035
Weather (5) 0.53846153846154
test (26) 0.98657718120805
XOR (7) 0.33333333333333
test (36) 0.98657718120805
test (23) 0.98657718120805
anneal (59) 0.60646599777035
test (28) 0.98657718120805
anneal (42) 0.60646599777035
anneal (33) 0.60646599777035
test (15) 0.98657718120805
anneal (37) 0.49386845039019
anneal (53) 0.60646599777035
anneal (25) 0.60646599777035
anneal (56) 0.49386845039019
test (39) 0.98657718120805
TEST2fe1e97c97-pandas_testing_dataset (1) 0
test (35) 0.98657718120805
test (29) 0.98657718120805
test (31) 0.98657718120805
anneal (52) 0.60646599777035
Diabetes(scikit-learn) (4) -84.637188208617
anneal (54) 0.60646599777035
Weather (7) 0.53846153846154
test (22) 0.98657718120805
test (38) 0.98657718120805
test (32) 0.98657718120805
test (18) 0.98657718120805
Diabetes(scikit-learn) (2) -84.637188208617
TESTeab2945786-NumPy_testing_dataset (1) 0
vineyard (1) -1.1764705882353
pol (1) -39.418694579639
anneal (31) 0.60646599777035
Weather (9) 0.53846153846154
Diabetes(scikit-learn) (5) -84.637188208617
TESTccda34c750-pandas_testing_dataset (1) 0.75
cnae-9 (1) 0
one-hundred-plants-margin (1) 0.93808630393996
anneal (74) 0.60646599777035
Weather (11) 0.53846153846154
anneal (61) 0.60646599777035
test (17) 0.98657718120805
TEST22dd0ebd9b-ModifiedWeather (1) 0.53846153846154
anneal (36) 0.60646599777035
test (43) 0.98657718120805
XOR (9) 0.33333333333333
anneal (89) 0.60646599777035
TESTee7d03de92-pandas_testing_dataset (1) 0.75
anneal (77) 0.60646599777035
anneal (84) 0.60646599777035
TEST76d8cfa095-pandas_testing_dataset (1) 0
XOR (10) 0.33333333333333
TESTaf3b61833a-NumPy_testing_dataset (1) 0
TEST9aca640b6e-NumPy_testing_dataset (1) 0
blood-transfusion-service-center (1) 0.73092369477912
autoMpg (1) -2.8831234256927
autoPrice (1) -2423.0696202532
quake (1) 0.80418006430868
pbc (1) -1003.4172661871
TEST5f1dfbd75d-pandas_testing_dataset (1) 0
anneal (95) 0.60646599777035
anneal (80) 0.60646599777035
test (40) 0.98657718120805
TESTda410c34dc-pandas_testing_dataset (2) 0
TEST398fcda80b-ModifiedWeather (1) 0.53846153846154
TEST7e318eb969-pandas_testing_dataset (3) 0
Weather (10) 0.53846153846154
test (41) 0.98657718120805
TEST76d8cfa095-pandas_testing_dataset (3) 0
test (49) 0.98657718120805
Diabetes(scikit-learn) (6) -84.637188208617
TESTda410c34dc-pandas_testing_dataset (3) 0
TEST5f1dfbd75d-pandas_testing_dataset (3) 0
TEST5705382a07-UploadTestWithURL (1)
TESTccda34c750-pandas_testing_dataset (2) 0.33333333333333
TEST5f1dfbd75d-pandas_testing_dataset (2) 0
XOR (14) 0.33333333333333
XOR (11) 0.33333333333333
TEST5f1dfbd75d-pandas_testing_dataset (4) 0
anneal (83) 0.60646599777035
TEST2fb3e3c09b-XOR (1) 0.33333333333333
anneal (101) 0.60646599777035
anneal (92) 0.60646599777035
anneal (75) 0.60646599777035
XOR (8) 0.33333333333333
Weather (14) 0.53846153846154
TESTccda34c750-pandas_testing_dataset (3) 0
test (42) 0.98657718120805
test (30) 0.98657718120805
XOR (13) 0.33333333333333
anneal (103) 0.60646599777035
Weather (12) 0.53846153846154
anneal (90) 0.60646599777035
anneal (73) 0.60646599777035
anneal (88) 0.49386845039019
TESTe2a3b91028-ModifiedWeather (1) 0.53846153846154
TESTf7444a8ea4-pandas_testing_dataset (3) 0
TEST07c2b360c0-pandas_testing_dataset (3) 0
TEST7e318eb969-pandas_testing_dataset (2) 0.33333333333333
test (47) 0.98657718120805
test (50) 0.98657718120805
TESTda410c34dc-pandas_testing_dataset (1) 0
anneal (98) 0.60646599777035
test (37) 0.98657718120805
anneal (86) 0.49386845039019
anneal (105) 0.49386845039019
anneal (87) 0.60646599777035
anneal (99) 0.60646599777035
test (44) 0.98657718120805
TESTcf74ef9481-XOR (1) 0.33333333333333
XOR (12) 0.33333333333333
test (51) 0.98657718120805
anneal (91) 0.040902045102255
test (46) 0.98657718120805
test (45) 0.98657718120805
test (52) 0.98657718120805
anneal (44) 0.60646599777035
anneal (79) 0.60646599777035
anneal (28) 0.60646599777035
test (48) 0.98657718120805
TEST7e318eb969-pandas_testing_dataset (1) 0.75
TESTda410c34dc-pandas_testing_dataset (4) 0
TEST07c2b360c0-pandas_testing_dataset (2) 0.33333333333333
TESTdcaa77be46-XOR (1) 0.33333333333333
TEST8eecdebbd6-XOR (1) 0.33333333333333
anneal (102) 0.60646599777035
Diabetes(scikit-learn) (7) -84.637188208617
anneal (97) 0.60646599777035
TEST2302efba1e-XOR (1) 0.33333333333333
anneal (72) 0.49386845039019
test (34) 0.98657718120805
TEST07c2b360c0-pandas_testing_dataset (1) 0.75
Weather (13) 0.53846153846154
TESTc09922bc0f-XOR (1) 0.33333333333333
test (25) 0.98657718120805
TEST76d8cfa095-pandas_testing_dataset (2) 0
TEST76d8cfa095-pandas_testing_dataset (4) 0
cylinder-bands (2) 0.81076066790353
diabetes_numeric (1) 0.19761904761905
semeion (1) 0.92525125628141
anneal (11) 0.60646599777035
anneal (106) 0.60646599777035
anneal (115) 0.49386845039019
XOR (18) 0.33333333333333
anneal (116) 0.040902045102255
anneal (113) 0.60646599777035
anneal (107) 0.60646599777035
mfeat-zernike (1) 0.99549774887444
Bioresponse (1) 0.49626666666667
kr-vs-kp (1) 0.99906103286385
lowbwt (1) -44.393617021277
anneal (82) 0.60646599777035
anneal (114) 0.60646599777035
Diabetes(scikit-learn) (9) -84.637188208617
Diabetes(scikit-learn) (8) -84.637188208617
Diabetes(scikit-learn) (10) -84.637188208617
credit-a (1) 0.97822931785196
anneal (119) 0.60646599777035
anneal (118) 0.60646599777035
XOR (21) 0.33333333333333
Weather (17) 0.53846153846154
Weather (21) 0.53846153846154
XOR (23) 0.33333333333333
XOR (19) 0.33333333333333
XOR (17) 0.33333333333333
XOR (16) 0.33333333333333
XOR (24) 0.33333333333333
Diabetes(scikit-learn) (11) -84.637188208617
profb (1) 0.54545454545455
climate-model-simulation-crashes (1) 0.83858998144712
pendigits (1) 0.10290237467018
tic-tac-toe (1) 0.99895506792059
abalone (1) 0.20641762452107
delta_elevators (1) 0.99717276166456
MiceProtein (1) 0.9935125115848
anneal (108) 0.60646599777035
artificial-characters (1) 0.99823823040031
cloud (1) -0.0081308411214952
mushroom (1) 0.72633263572572
anneal (141) 0.60646599777035
Weather (18) 0.53846153846154
anneal (147) 0.60646599777035
anneal (136) 0.60646599777035
anneal (135) 0.49386845039019
anneal (122) 0.49386845039019
XOR (22) 0.33333333333333
Weather (22) 0.53846153846154
anneal (112) 0.60646599777035
XOR (29) 0.33333333333333
anneal (128) 0.60646599777035
anneal (139) 0.60646599777035
XOR (27) 0.33333333333333
eucalyptus (1) 0.39319727891156
PhishingWebsites (1) 0.51402207345757
one-hundred-plants-shape (1) 0.93808630393996
cholesterol (1) -58.059602649007
texture (1) 0.99818148754319
fourclass_scale (1) 0.094076655052265
credit-g (1) 0.56956956956957
anneal (151) 0.60646599777035
anneal (132) 0.60646599777035
anneal (156) 0.60646599777035
anneal (134) 0.60646599777035
anneal (149) 0.60646599777035
Weather (16) 0.53846153846154
Weather (15) 0.53846153846154
Weather (27) 0.53846153846154
anneal (126) 0.60646599777035
anneal (167) 0.60646599777035
anneal (127) 0.60646599777035
anneal (131) 0.60646599777035
anneal (124) 0.49386845039019
Diabetes(scikit-learn) (15) -84.637188208617
Diabetes(scikit-learn) (14) -84.637188208617
anneal (143) 0.60646599777035
anneal (121) 0.60646599777035
anneal (146) 0.60646599777035
anneal (158) 0.60646599777035
anneal (120) 0.60646599777035
anneal (117) 0.49386845039019
Weather (24) 0.53846153846154
Diabetes(scikit-learn) (12) -84.637188208617
XOR (31) 0.33333333333333
anneal (150) 0.60646599777035
XOR (32) 0.33333333333333
Weather (23) 0.53846153846154
anneal (160) 0.60646599777035
Diabetes(scikit-learn) (17) -84.637188208617
anneal (155) 0.60646599777035
Weather (30) 0.53846153846154
anneal (110) 0.60646599777035
anneal (173) 0.49386845039019
Weather (20) 0.53846153846154
TEST569e152152-pandas_testing_dataset (2) 0.33333333333333
XOR (33) 0.33333333333333
Weather (26) 0.53846153846154
Weather (28) 0.53846153846154
XOR (15) 0.33333333333333
anneal (137) 0.49386845039019
Weather (19) 0.53846153846154
anneal (144) 0.60646599777035
XOR (25) 0.33333333333333
anneal (166) 0.49386845039019
XOR (30) 0.33333333333333
anneal (159) 0.60646599777035
anneal (161) 0.60646599777035
anneal (154) 0.60646599777035
anneal (125) 0.60646599777035
Weather (31) 0.53846153846154
Weather (34) 0.53846153846154
anneal (168) 0.60646599777035
anneal (172) 0.60646599777035
anneal (140) 0.60646599777035
anneal (129) 0.60646599777035
anneal (174) 0.60646599777035
XOR (20) 0.33333333333333
Weather (25) 0.53846153846154
Diabetes(scikit-learn) (16) -84.637188208617
XOR (34) 0.33333333333333
XOR (28) 0.33333333333333
anneal (162) 0.60646599777035
anneal (109) 0.60646599777035
anneal (171) 0.60646599777035
anneal (164) 0.60646599777035
anneal (145) 0.60646599777035
anneal (123) 0.49386845039019
Weather (33) 0.53846153846154
Diabetes(scikit-learn) (13) -84.637188208617
XOR (26) 0.33333333333333
anneal (152) 0.60646599777035
anneal (169) 0.60646599777035
anneal (142) 0.49386845039019
Weather (29) 0.53846153846154
Weather (32) 0.53846153846154
TESTd643aafd62-NumPy_testing_dataset (1) 0
TEST63cd902071-pandas_testing_dataset (2) 0
anneal (175) 0.60646599777035
TESTe55d2d0c3d-pandas_testing_dataset (2) 0.33333333333333
anneal (177) 0.60646599777035
TESTe55d2d0c3d-pandas_testing_dataset (3) 0
anneal (178) 0.040902045102255
TEST9d96ec7ade-UploadTestWithURL (1)
anneal (180) 0.60646599777035
TESTcf61db30f6-pandas_testing_dataset (1) 0.75
anneal (181) 0.60646599777035
TEST63cd902071-pandas_testing_dataset (4) 0
TEST63cd902071-pandas_testing_dataset (3) 0
TESTada3067c77-XOR (1) 0.33333333333333
TESTf112d7f8be-XOR (1) 0.33333333333333
TEST9ecb165245-UploadTestWithURL (1)
anneal (179) 0.60646599777035
TESTaebada2a36-ModifiedWeather (1) 0.53846153846154
TESTe55d2d0c3d-pandas_testing_dataset (1) 0.75
TEST63cd902071-pandas_testing_dataset (1) 0
anneal (182) 0.60646599777035
anneal (183) 0.60646599777035
anneal (184) 0.60646599777035
mfeat-pixel (1) 0.99549774887444
madelon (1) 0.5105809926895
cleveland (1) -0.22516556291391
mfeat-karhunen (1) 0.99549774887444
isolet (1) 0.30002565418163
mozilla4 (1) 0.71307256819352
anneal (185) 0.60646599777035
Weather (35) 0.53846153846154
anneal (190) 0.60646599777035
anneal (187) 0.60646599777035
anneal (192) 0.60646599777035
anneal (191) 0.49386845039019
Weather (36) 0.53846153846154
XOR (36) 0.33333333333333
bank-marketing (1) 0.84308781243088
musk (1) 0.99984841594664
sylva_agnostic (1) 0.88495206335973
pc3 (1) 0.81434058898848
wisconsin (1) -29.740932642487
anneal (186) 0.60646599777035
anneal (189) 0.60646599777035
Diabetes(scikit-learn) (18) -84.637188208617
XOR (35) 0.33333333333333
NumPy_testing_dataset (1) 0
anneal (193) 0.040902045102255
ModifiedWeather (1) 0.53846153846154
XOR (37) 0.33333333333333
XOR (38) 0.33333333333333
UploadTestWithURL (1)
UploadTestWithURL (2)
anneal (195) 0.60646599777035
anneal (198) 0.60646599777035
anneal (194) 0.60646599777035
anneal (201) 0.60646599777035
Weather (38) 0.53846153846154
XOR (39) 0.33333333333333
Weather (37) 0.53846153846154
Diabetes(scikit-learn) (19) -84.637188208617
anneal (199) 0.60646599777035
anneal (196) 0.60646599777035
anneal (200) 0.49386845039019
XOR (40) 0.33333333333333
UNIX_user_data (1) 0.99912078250357
anneal (176) 0.60646599777035
mfeat-fourier (1) 0.99549774887444
car (1) 0.59930515344528
splice (1) 0.99937284415177
vehicle (1) 0.25798816568047
electricity (1) 0.85330273002141
anneal (208) 0.60646599777035
anneal (202) 0.60646599777035
anneal (206) 0.49386845039019
Weather (39) 0.53846153846154
XOR (42) 0.33333333333333
anneal (203) 0.60646599777035
anneal (209) 0.60646599777035
anneal (207) 0.60646599777035
anneal (204) 0.60646599777035
Weather (40) 0.53846153846154
Diabetes(scikit-learn) (20) -84.637188208617
XOR (41) 0.33333333333333
har (1) 0.96125461254613
hill-valley (1) 0.50949628406276
micro-mass (2) 0.69824561403509
detroit (1) -29.0975
mfeat-morphological (1) 0.99549774887444
sick (1) 0.88650225404402
LED-display-domain-7digit (1) 0.72144288577154
scene (1) 0.98462177888612
auto_price (1) -2423.0696202532
breast-w (1) 0.63180515759312
anneal (94) 0.60646599777035
anneal (213) 0.60646599777035
anneal (215) 0.60646599777035
Diabetes(scikit-learn) (21) -84.637188208617
Weather (42) 0.53846153846154
Weather (41) 0.53846153846154
XOR (43) 0.33333333333333
anneal (211) 0.60646599777035
anneal (210) 0.60646599777035
anneal (214) 0.60646599777035
anneal (212) 0.60646599777035
anneal (218) 0.49386845039019
XOR (44) 0.33333333333333
segment (1) 0.14811606756172
anneal (222) 0.60646599777035
Weather (43) 0.53846153846154
anneal (220) 0.60646599777035
XOR (46) 0.33333333333333
anneal (224) 0.60646599777035
anneal (226) 0.60646599777035
anneal (219) 0.60646599777035
Diabetes(scikit-learn) (22) -84.637188208617
XOR (45) 0.33333333333333
anneal (221) 0.60646599777035
anneal (225) 0.49386845039019
Weather (44) 0.53846153846154
monks-problems-1 (1) 0.81621621621622
irish (1) 0.60921843687375
gina_agnostic (1) 0.50014421690222
MagicTelescope (1) 0.99994742100005
fruitfly (1) -16.653225806452
cjs (3) 0.99821109123435
dresses-sales (2) 0.47294589178357
jm1 (1) 0.99981624402793
mfeat-factors (1) 0.99549774887444
balance-scale (1) 0.69711538461538
optdigits (1) 0.0925431571454
letter (1) 0.040902045102255
cmc (1) 0.99660326086957
soybean (1) 0.94574780058651
pc1 (1) 0.99819494584838
banknote-authentication (1) 0.99927060539752
cardiotocography (1) 0.608
gas-drift (1) 0.59199079732547
ilpd (1) 0.61340206185567
ozone-level-8hr (1) 0.91551519936834
phoneme (1) 0.59189339255969
tamilnadu-electricity (1) 0.99958497160332
wilt (1) 0.96548160396858
mbagrade (1) 0.66205
sleep (1) -0.47540983606557
vowel (2) 0
synthetic_control (1) 0.99165275459099
kc1 (1) 0.99905123339658
wall-robot-navigation (1) 0.9275893675527
steel-plates-fault (1) 0.99948453608247
Amazon_employee_access (1) 0.8914794921875
GesturePhaseSegmentationProcessed (1) 0.96059562398703
kin8nm (1) 0.70217177769186
qsar-biodeg (1) 0.99715370018975
satimage (1) 0.18743194898118
nomao (1) 0.94832288765088
Click_prediction_small (5) 0.71702505820212
anneal (234) 0.60646599777035
Diabetes(scikit-learn) (23) -84.637188208617
anneal (244) 0.49386845039019
XOR (50) 0.33333333333333
anneal (228) 0.60646599777035
anneal (237) 0.60646599777035
anneal (242) 0.60646599777035
anneal (231) 0.49386845039019
Weather (47) 0.53846153846154
Weather (45) 0.53846153846154
TEST08f51af3c8-pandas_testing_dataset (1) 0.75
TESTa365aee568-UploadTestWithURL (1)
anneal (233) 0.60646599777035
anneal (240) 0.60646599777035
anneal (229) 0.60646599777035
TEST037907c164-pandas_testing_dataset (3) 0
TESTa540f38c2d-pandas_testing_dataset (1) 0
TESTfd496f5b4d-XOR (1) 0.33333333333333
TEST037907c164-pandas_testing_dataset (2) 0.33333333333333
XOR (47) 0.33333333333333
XOR (48) 0.33333333333333
TEST82462bce44-UploadTestWithURL (1)
XOR (49) 0.33333333333333
anneal (241) 0.60646599777035
anneal (227) 0.60646599777035
anneal (236) 0.60646599777035
TESTa540f38c2d-pandas_testing_dataset (4) 0
Weather (46) 0.53846153846154
Weather (48) 0.53846153846154
anneal (235) 0.040902045102255
TESTa540f38c2d-pandas_testing_dataset (2) 0
TESTa540f38c2d-pandas_testing_dataset (3) 0
anneal (238) 0.60646599777035
Diabetes(scikit-learn) (24) -84.637188208617
GermanCreditModified (1) 0.57957957957958
GermanCreditModified (3) 0.57957957957958
GermanCreditModified (2) 0.57957957957958
TEST062fea70c5-XOR (1) 0.33333333333333
anneal (249) 0.60646599777035
Weather (50) 0.53846153846154
anneal (246) 0.60646599777035
anneal (251) 0.60646599777035
anneal (252) 0.60646599777035
anneal (247) 0.60646599777035
anneal (245) 0.60646599777035
XOR (51) 0.33333333333333
anneal (250) 0.49386845039019
Weather (49) 0.53846153846154
Diabetes(scikit-learn) (25) -84.637188208617
XOR (52) 0.33333333333333
ada_agnostic (1) 0.62639771979829
pc4 (1) 0.78037062457104
first-order-theorem-proving (1) 0.36782736635606
one-hundred-plants-texture (1) 0.93804755944931
wdbc (1) 0.625
pharynx (1) -455.46907216495
analcatdata_dmft (1) 0.99371859296482
Australian (3) 0.51959361393324
waveform-5000 (1) 0.33206641328266
monks-problems-2 (1) 0.44
JapaneseVowels (1) 0.99829317269076
adult (2) 0.63442599455376
anneal (232) 0.60646599777035
monks-problems-3 (1) 0.77034358047016
analcatdata_authorship (1) 0.99642857142857
diabetes (1) 0.55019556714472
eeg-eye-state (1) 0.99846451699045
collins (1) 0.97194388777555
kc2 (1) 0.99424184261036
anneal (253) 0.60646599777035
anneal (255) 0.60646599777035
anneal (257) 0.60646599777035
anneal (260) 0.49386845039019
Weather (52) 0.53846153846154
anneal (1) 0.60646599777035
Diabetes(scikit-learn) (26) -84.637188208617
longley (1) -1223.2666666667
iris (1) 0.98657718120805
anneal (259) 0.60646599777035
anneal (258) 0.60646599777035
XOR (54) 0.33333333333333
Weather (51) 0.53846153846154
XOR (53) 0.33333333333333
anneal (254) 0.60646599777035