Dataset # of Instances # of Missing Values # of Numeric Attributes # of Categorical Attributes # of Classes % of Majority Class
abalone_1 4177 0 7 2 29 16.5
abalone_2 4177 0 7 2 2 50.18
abalone_3 4177 0 7 2 3 34.64
acute-inflammations_1 120 0 1 6 2 58.33
acute-inflammations_2 120 0 1 6 2 50.83
ada_agnostic_1 4562 0 48 1 2 75.19
ada_prior_1 4562 88 6 9 2 75.19
analcatdata_apnea1_2 475 0 1 3 2 87.16
analcatdata_apnea2_2 475 0 1 3 2 86.53
analcatdata_apnea3_2 450 0 1 3 2 87.78
analcatdata_asbestos_1 83 0 1 3 3 54.22
analcatdata_authorship_1 841 0 70 1 4 37.69
analcatdata_authorship_2 841 0 70 1 2 62.31
analcatdata_bankruptcy_1 50 0 5 2 2 50
analcatdata_birthday_2 365 30 1 3 2 85.48
analcatdata_bondrate_1 57 1 4 8 5 57.89
analcatdata_bondrate_2 57 1 4 8 2 57.89
analcatdata_boxing1_1 120 0 0 4 2 65
analcatdata_boxing2_1 132 0 0 4 2 53.79
analcatdata_broadwaymult_1 285 27 3 5 7 41.4
analcatdata_broadwaymult_2 285 27 3 5 2 58.6
analcatdata_broadway_1 95 9 3 7 5 71.58
analcatdata_broadway_2 95 9 3 7 2 71.58
analcatdata_challenger_1 23 0 1 5 2 56.52
analcatdata_challenger_2 138 0 1 2 2 93.48
analcatdata_chlamydia_2 100 0 0 4 2 81
analcatdata_creditscore_1 100 0 3 4 2 73
analcatdata_cyyoung8092_1 97 0 7 4 2 75.26
analcatdata_cyyoung9302_1 92 0 6 5 2 79.35
analcatdata_dmft_1 797 0 0 5 6 19.45
analcatdata_dmft_2 797 0 0 5 2 80.55
analcatdata_draft_1 366 2 3 3 12 8.74
analcatdata_draft_2 366 1 3 3 2 91.26
analcatdata_election2000_2 67 0 14 2 2 73.13
analcatdata_germangss_2 400 0 0 6 2 77.5
analcatdata_gsssexsurvey_2 159 6 4 6 2 77.99
analcatdata_gviolence_2 74 0 8 2 2 58.11
analcatdata_halloffame_2 1340 20 15 3 2 90.67
analcatdata_homerun_1 163 9 13 15 2 94.48
analcatdata_impeach_1 100 0 2 9 2 62
analcatdata_lawsuit_1 264 0 3 2 2 92.8
analcatdata_marketing_1 364 101 0 33 5 31.59
analcatdata_marketing_2 364 80 0 33 2 68.41
analcatdata_michiganacc_2 108 0 2 3 2 55.56
analcatdata_neavote_2 100 0 1 3 2 93
analcatdata_negotiation_2 92 26 4 2 2 71.74
analcatdata_olympic2000_2 66 0 11 2 2 50
analcatdata_reviewer_1 379 1418 0 9 3 43.01
analcatdata_reviewer_2 379 1368 0 9 2 56.99
analcatdata_runshoes_2 60 14 4 7 2 60
analcatdata_seropositive_2 132 0 2 2 2 65.15
analcatdata_supreme_2 4052 0 7 1 2 76.04
analcatdata_uktrainacc_2 31 150 16 1 2 87.1
analcatdata_vehicle_2 48 0 0 5 2 56.25
analcatdata_vineyard_2 468 0 2 2 2 55.56
analcatdata_whale_1 228 20 6 2 2 50.88
analcatdata_wildcat_2 163 0 3 3 2 71.17
anneal_1 898 22175 6 33 6 76.17
anneal_3 898 22175 6 33 2 76.17
appendicitis_1 106 0 7 1 2 80.19
ar1_1 121 0 29 1 2 92.56
ar3_1 63 0 29 1 2 87.3
ar4_1 107 0 29 1 2 81.31
ar5_1 36 0 29 1 2 77.78
ar6_1 101 0 29 1 2 85.15
arrhythmia_1 452 408 206 74 16 54.2
arrhythmia_2 452 408 206 74 2 54.2
arsenic-female-bladder_2 559 0 3 2 2 85.69
arsenic-female-lung_2 559 0 3 2 2 96.6
arsenic-male-bladder_2 559 0 3 2 2 95.71
arsenic-male-lung_2 559 0 3 2 2 97.67
artificial-characters_1 10218 0 7 1 10 13.86
audiology_1 226 317 0 70 24 25.22
audiology_2 226 317 0 70 2 74.78
auto93_2 93 14 16 7 2 62.37
autoHorse_2 205 57 17 9 2 59.51
autoMpg_2 398 6 4 4 2 52.51
autoPrice_2 159 0 15 1 2 66.04
autos_1 205 59 15 11 7 32.68
autos_2 205 59 15 11 2 67.32
autoUniv-au1-1000_1 1000 0 20 1 2 74.1
autoUniv-au4-2500_1 2500 0 58 43 3 46.92
autoUniv-au6-1000_1 1000 0 37 4 8 24
autoUniv-au6-400_1 400 0 37 4 8 27.75
autoUniv-au6-750_1 750 0 37 4 8 22
autoUniv-au7-1100_1 1100 0 8 5 5 27.73
autoUniv-au7-500_1 500 0 8 5 5 38.4
autoUniv-au7-700_1 700 0 8 5 3 35
auto_price_2 159 0 14 2 2 66.04
BachChoralHarmony_1 5665 0 2 15 102 8.88
backache_1 180 0 6 27 2 86.11
badges2_1 294 0 8 4 2 71.43
balance-scale_1 625 0 4 1 3 46.08
balance-scale_2 625 0 4 1 2 53.92
balloon_2 2001 0 2 1 2 75.91
banana_1 5300 0 2 1 2 55.17
bank-marketing_2 4521 0 7 10 2 88.48
bank8FM_2 8192 0 8 1 2 59.63
banknote-authentication_1 1372 0 4 1 2 55.54
baskball_2 96 0 4 1 2 51.04
biomed_1 209 15 7 2 2 64.11
blogger_1 100 0 0 6 2 68
blood-transfusion-service-center_1 748 0 4 1 2 76.2
bodyfat_2 252 0 14 1 2 50.79
bolts_2 40 0 7 1 2 65
boston_2 506 0 11 3 2 58.7
boston_corrected_2 506 0 17 4 2 55.93
braziltourism_1 412 96 4 5 7 77.18
braziltourism_2 412 96 4 5 2 77.18
breast-cancer-dropped-missing-attributes-values_1 277 0 0 10 2 70.76
breast-cancer_1 286 9 0 10 2 70.28
breast-tissue_1 106 0 9 1 6 20.75
breast-tissue_2 106 0 9 1 4 46.23
breast-w_1 699 16 9 1 2 65.52
breastTumor_2 286 9 1 9 2 58.04
bridges_1 107 73 3 10 6 41.12
bridges_2 107 73 0 13 6 41.12
bridges_3 105 61 3 10 6 41.9
bridges_4 105 61 0 13 6 41.9
bridges_5 107 71 3 10 2 58.88
cal_housing_1 20640 0 8 1 2 59.38
cardiotocography_1 2126 0 35 1 10 27.23
cardiotocography_2 2126 0 35 1 3 77.85
cars_1 406 14 6 3 3 62.56
cars_2 406 14 6 3 2 62.56
car_1 1728 0 0 7 4 70.02
car_2 1728 0 0 7 2 70.02
CastMetal1_1 327 0 37 1 2 87.16
chatfield_4_2 235 0 12 1 2 60.43
chess_1 28056 0 1 7 18 16.23
cholesterol_2 303 6 6 8 2 54.79
chscase_adopt_2 39 0 2 2 2 69.23
chscase_census2_2 400 0 7 1 2 50.75
chscase_census3_2 400 0 7 1 2 52
chscase_census4_2 400 0 7 1 2 51.5
chscase_census5_2 400 0 7 1 2 51.75
chscase_census6_2 400 0 6 1 2 58.75
chscase_funds_2 185 0 2 2 2 52.97
chscase_geyser1_2 222 0 2 1 2 60.36
chscase_health_2 50 0 2 3 2 52
chscase_vine1_2 52 0 9 1 2 53.85
chscase_vine2_2 468 0 2 1 2 54.7
chscase_whale_2 228 20 9 1 2 51.32
cjs_2 2796 68100 32 3 2 75.68
cleveland_2 303 6 6 8 2 54.13
climate-model-simulation-crashes_1 540 0 20 1 2 91.48
cloud_2 108 0 6 2 2 70.37
cm1_req_1 89 0 7 2 2 77.53
cmc_1 1473 0 2 8 3 42.7
cmc_2 1473 0 2 8 2 57.3
colic_1 368 1927 7 21 2 66.3
colic_2 368 1927 7 16 2 63.04
colleges_aaup_2 1161 256 13 4 2 70.03
colleges_usnews_2 1302 7830 32 3 2 52.84
collins_1 500 0 20 4 15 16
collins_2 500 0 20 4 2 84
confidence_2 72 0 3 1 2 83.33
contact-lenses_1 24 0 0 5 3 62.5
CostaMadre1_2 296 0 37 1 2 87.16
cpu_2 209 0 6 2 2 74.64
cpu_act_3 8192 0 21 1 2 69.76
cpu_small_3 8192 0 12 1 2 69.76
credit-a_1 690 67 6 10 2 55.51
credit-g_1 1000 0 7 14 2 70
datatrieve_1 130 0 8 1 2 91.54
data_1 898 0 6 26 5 76.17
dbworld-subjects-stemmed_1 64 0 0 230 2 54.69
dbworld-subjects_1 64 0 0 243 2 54.69
delta_ailerons_1 7129 0 5 1 2 53.06
delta_elevators_3 9517 0 6 1 2 50.28
dermatology_1 366 8 1 34 6 30.6
dermatology_2 366 8 1 34 2 69.4
desharnais_1 81 0 11 1 3 56.79
desharnais_2 81 0 12 1 3 56.79
diabetes_1 768 0 8 1 2 65.1
diabetes_numeric_2 43 0 2 1 2 60.47
diggle_table_a1_2 48 0 4 1 2 52.08
diggle_table_a2_2 310 0 7 2 2 53.23
disclosure_x_bias_2 662 0 3 1 2 52.11
disclosure_x_noise_2 662 0 3 1 2 50.3
disclosure_x_tampered_2 662 0 3 1 2 50.6
disclosure_z_2 662 0 3 1 2 52.57
dresses-sales_1 500 0 1 12 2 58
dresses-sales_2 500 835 1 12 2 58
echoMonths_2 130 97 6 4 2 50.77
ecoli_1 336 0 7 1 8 42.56
ecoli_2 336 0 7 1 2 57.44
elusage_2 55 0 1 2 2 56.36
energy-efficiency_1 768 0 8 2 38 10.03
Engine1_1 383 0 5 1 3 67.1
eucalyptus_1 736 448 14 6 5 29.08
eucalyptus_2 736 448 14 6 2 70.92
fertility_1 100 0 9 1 2 88
fishcatch_2 158 87 5 3 2 60.13
fl2000_2 67 0 14 2 2 61.19
flags_1 194 0 2 28 8 35.57
flags_2 194 0 2 28 2 64.43
fri_c0_1000_10_2 1000 0 10 1 2 50.9
fri_c0_1000_25_2 1000 0 25 1 2 50.3
fri_c0_1000_50_2 1000 0 50 1 2 51
fri_c0_1000_5_2 1000 0 5 1 2 50.3
fri_c0_100_10_2 100 0 10 1 2 55
fri_c0_100_25_2 100 0 25 1 2 50
fri_c0_100_50_2 100 0 50 1 2 51
fri_c0_100_5_2 100 0 5 1 2 54
fri_c0_250_10_2 250 0 10 1 2 50
fri_c0_250_25_2 250 0 25 1 2 50.4
fri_c0_250_50_2 250 0 50 1 2 53.2
fri_c0_250_5_2 250 0 5 1 2 50
fri_c0_500_10_2 500 0 10 1 2 51.8
fri_c0_500_25_2 500 0 25 1 2 51
fri_c0_500_50_2 500 0 50 1 2 51.2
fri_c0_500_5_2 500 0 5 1 2 50.2
fri_c1_1000_10_2 1000 0 10 1 2 56.4
fri_c1_1000_25_2 1000 0 25 1 2 54.6
fri_c1_1000_50_2 1000 0 50 1 2 54.7
fri_c1_1000_5_2 1000 0 5 1 2 54.3
fri_c1_100_10_2 100 0 10 1 2 53
fri_c1_100_25_2 100 0 25 1 2 53
fri_c1_100_50_2 100 0 50 1 2 56
fri_c1_100_5_2 100 0 5 1 2 55
fri_c1_250_10_2 250 0 10 1 2 56
fri_c1_250_25_2 250 0 25 1 2 57.2
fri_c1_250_50_2 250 0 50 1 2 54.8
fri_c1_250_5_2 250 0 5 1 2 52.4
fri_c1_500_10_2 500 0 10 1 2 54.8
fri_c1_500_25_2 500 0 25 1 2 53.4
fri_c1_500_50_2 500 0 50 1 2 52.4
fri_c1_500_5_2 500 0 5 1 2 53.4
fri_c2_1000_10_2 1000 0 10 1 2 58
fri_c2_1000_25_2 1000 0 25 1 2 56.3
fri_c2_1000_50_2 1000 0 50 1 2 58.2
fri_c2_1000_5_2 1000 0 5 1 2 58.4
fri_c2_100_10_2 100 0 10 1 2 55
fri_c2_100_25_2 100 0 25 1 2 57
fri_c2_100_50_2 100 0 50 1 2 58
fri_c2_100_5_2 100 0 5 1 2 60
fri_c2_250_10_2 250 0 10 1 2 63.6
fri_c2_250_25_2 250 0 25 1 2 55.6
fri_c2_250_50_2 250 0 50 1 2 54.8
fri_c2_250_5_2 250 0 5 1 2 56
fri_c2_500_10_2 500 0 10 1 2 57.2
fri_c2_500_25_2 500 0 25 1 2 60.8
fri_c2_500_50_2 500 0 50 1 2 59
fri_c2_500_5_2 500 0 5 1 2 59.6
fri_c3_1000_10_2 1000 0 10 1 2 56
fri_c3_1000_25_2 1000 0 25 1 2 55.7
fri_c3_1000_50_2 1000 0 50 1 2 55.5
fri_c3_1000_5_2 1000 0 5 1 2 56.3
fri_c3_100_10_2 100 0 10 1 2 60
fri_c3_100_25_2 100 0 25 1 2 55
fri_c3_100_50_2 100 0 50 1 2 62
fri_c3_100_5_2 100 0 5 1 2 56
fri_c3_250_10_2 250 0 10 1 2 54
fri_c3_250_25_2 250 0 25 1 2 55.6
fri_c3_250_50_2 250 0 50 1 2 56.8
fri_c3_250_5_2 250 0 5 1 2 56.4
fri_c3_500_10_2 500 0 10 1 2 54.4
fri_c3_500_25_2 500 0 25 1 2 56
fri_c3_500_50_2 500 0 50 1 2 56.4
fri_c3_500_5_2 500 0 5 1 2 52.6
fri_c4_1000_100_2 1000 0 100 1 2 56.4
fri_c4_1000_10_2 1000 0 10 1 2 56
fri_c4_1000_25_2 1000 0 25 1 2 54.7
fri_c4_1000_50_2 1000 0 50 1 2 56
fri_c4_100_100_2 100 0 100 1 2 53
fri_c4_100_10_2 100 0 10 1 2 53
fri_c4_100_25_2 100 0 25 1 2 54
fri_c4_100_50_2 100 0 50 1 2 56
fri_c4_250_100_2 250 0 100 1 2 56
fri_c4_250_10_2 250 0 10 1 2 53.2
fri_c4_250_25_2 250 0 25 1 2 54.4
fri_c4_250_50_2 250 0 50 1 2 54
fri_c4_500_100_2 500 0 100 1 2 56.6
fri_c4_500_10_2 500 0 10 1 2 55.2
fri_c4_500_25_2 500 0 25 1 2 56.8
fri_c4_500_50_2 500 0 50 1 2 52.8
fruitfly_2 125 0 2 3 2 60.8
glass_1 214 0 9 1 7 35.51
glass_2 214 0 9 1 2 64.49
grub-damage_1 155 0 2 7 4 31.61
grub-damage_2 155 0 2 7 2 68.39
haberman_1 306 0 2 2 2 73.53
hayes-roth_1 160 0 4 1 4 40.63
hayes-roth_2 132 0 4 1 2 61.36
heart-c_1 303 7 6 8 5 54.46
heart-c_2 303 7 6 8 2 54.46
heart-h_1 294 782 6 8 5 63.95
heart-h_3 294 0 13 1 5 63.95
heart-long-beach_1 200 0 13 1 5 28
heart-statlog_1 270 0 13 1 2 55.56
heart-switzerland_1 123 0 12 1 5 39.02
hepatitis_1 155 167 6 14 2 79.35
hill-valley_1 1212 0 100 1 2 50
hip_2 54 120 7 1 2 51.85
houses_2 20640 0 8 1 2 56.81
housing_1 506 0 12 2 2 58.7
humandevel_2 130 0 2 2 2 50
hutsof99_child_witness_2 42 0 16 1 2 59.52
hutsof99_logis_2 70 0 3 5 2 51.43
hypothyroid_1 3772 6064 7 23 4 92.29
hypothyroid_2 3772 6064 7 23 2 92.29
ilpd_1 583 0 9 2 2 71.36
ionosphere_1 351 0 34 1 2 64.1
irish_1 500 32 2 4 3 65
iris_3 150 0 4 1 2 66.67
jEdit_4.0_4.2_1 274 0 8 1 2 51.09
jEdit_4.2_4.3_1 369 0 8 1 2 55.28
jm1_1 10885 25 21 1 2 80.65
kc1-binary_1 145 0 94 1 2 58.62
kc1-top5_1 145 0 94 1 2 94.48
kc1_1 2109 0 21 1 2 84.54
kc2_1 522 0 21 1 2 79.5
kc3_1 458 0 39 1 2 90.61
kdd_el_nino-small_2 782 466 6 3 2 64.96
kdd_synthetic_control_1 600 0 60 2 2 83.33
kidney_2 76 0 3 4 2 52.63
kin8nm_2 8192 0 8 1 2 50.88
KnuggetChase3_1 194 0 39 1 2 81.44
kr-vs-k_1 28056 0 3 4 18 16.23
kropt_1 28056 0 0 7 18 16.23
KungChi3_1 123 0 39 1 2 86.99
labor_1 57 326 8 9 2 64.91
leaf_1 340 0 15 1 30 4.71
LED-display-domain-7digit_1 500 0 7 1 10 11.4
letter-challenge-unlabeled_1 20000 10000 16 1 2 86.2
letter_1 20000 0 16 1 26 4.07
letter_2 20000 0 16 1 2 95.94
lowbwt_2 189 0 2 8 2 52.38
lsvt_1 126 0 310 1 2 66.67
lung-cancer_1 32 5 0 57 2 71.88
lymph_1 148 0 3 16 4 54.73
lymph_2 148 0 3 16 2 54.73
machine_cpu_2 209 0 6 1 2 73.21
mammography_1 11183 0 6 1 2 97.68
mbagrade_2 61 0 1 2 2 52.46
mc1_1 9466 0 38 1 2 99.28
mc2_1 161 0 39 1 2 67.7
meta_2 528 504 19 3 2 89.77
meta_all_1 71 0 62 1 6 59.15
meta_batchincremental_1 74 0 62 1 4 67.57
meta_ensembles_1 74 0 62 1 4 60.81
meta_instanceincremental_1 74 0 62 1 4 72.97
mfeat-morphological_1 2000 0 6 1 10 10
mfeat-morphological_2 2000 0 6 1 2 90
mfeat-pixel_1 2000 0 0 241 10 10
mfeat-pixel_2 2000 0 0 241 2 90
mfeat-zernike_2 2000 0 47 1 2 90
MindCave2_1 125 0 39 1 2 64.8
molecular-biology_promoters_1 106 0 0 59 4 32.08
molecular-biology_promoters_2 106 0 0 59 2 67.92
monks-problems-1_1 556 0 0 7 2 51.08
monks-problems-2_1 601 0 0 7 2 50.08
monks-problems-3_1 554 0 0 7 2 50.36
mozilla4_1 15545 0 5 1 2 67.14
mu284_2 284 0 10 1 2 50
mw1_1 403 0 37 1 2 92.31
newton_hema_2 140 0 2 2 2 50
no2_2 500 0 7 1 2 50.2
nursery_2 12960 0 0 9 2 66.67
nursery_3 12958 0 0 9 4 33.34
one-hundred-plants-margin_1 1600 0 64 1 100 1
one-hundred-plants-shape_1 1600 0 64 1 100 1
one-hundred-plants-texture_1 1599 0 64 1 100 1
optdigits_1 5620 0 64 1 10 10.18
optdigits_2 5620 0 64 1 2 89.82
ozone-level-8hr_1 2534 0 72 1 2 93.69
page-blocks_1 5473 0 10 1 5 89.77
page-blocks_2 5473 0 10 1 2 89.77
parkinsons_1 195 0 22 1 2 75.38
pasture_1 36 0 21 2 3 33.33
pasture_2 36 0 21 2 2 66.67
pbcseq_2 1945 1133 12 7 2 50.03
pbc_3 418 1239 10 9 2 55.02
pc1_1 1109 0 21 1 2 93.06
pc1_req_1 320 0 7 2 2 66.56
pc2_1 5589 0 36 1 2 99.59
pc3_1 1563 0 37 1 2 89.76
pendigits_1 10992 0 16 1 10 10.41
pendigits_2 10992 0 16 1 2 89.59
pharynx_2 195 2 1 11 2 62.05
PhishingWebsites_1 11055 0 0 31 2 55.69
phoneme_1 5404 0 5 1 2 70.65
PieChart1_1 705 0 37 1 2 91.35
PieChart2_1 745 0 36 1 2 97.85
PieChart3_1 1077 0 37 1 2 87.56
PizzaCutter1_1 661 0 37 1 2 92.13
PizzaCutter3_1 1043 0 37 1 2 87.82
planning-relax_1 182 0 12 1 2 71.43
plasma_retinol_2 315 0 10 4 2 57.78
pm10_2 500 0 7 1 2 50.8
pollen_2 3848 0 5 1 2 50
pollution_2 60 0 15 1 2 51.67
postoperative-patient-data_1 90 3 0 9 3 71.11
postoperative-patient-data_2 90 3 0 9 2 71.11
primary-tumor_1 339 225 0 18 22 24.78
primary-tumor_2 339 225 0 18 2 75.22
prnn_cushings_1 27 0 2 2 4 44.44
prnn_fglass_1 214 0 9 1 6 35.51
prnn_fglass_2 214 0 9 1 2 64.49
prnn_synth_1 250 0 2 1 2 50
prnn_viruses_1 61 0 10 9 4 63.93
puma8NH_2 8192 0 8 1 2 50.22
pwLinear_2 200 0 10 1 2 51.5
pyrim_2 74 0 27 1 2 58.11
qsar-biodeg_1 1055 0 41 1 2 66.26
qualitative-bankruptcy_1 250 0 0 7 2 57.2
rabe_131_2 50 0 5 1 2 58
rabe_148_2 66 0 5 1 2 50
rabe_166_2 40 0 2 1 2 52.5
rabe_176_2 70 0 4 1 2 50
rabe_265_2 51 0 6 1 2 58.82
rabe_266_2 120 0 2 1 2 52.5
rabe_97_2 46 0 3 2 2 54.35
ringnorm_1 7400 0 20 1 2 50.49
rmftsa_ctoarrivals_2 264 0 1 2 2 61.74
rmftsa_ladata_2 508 0 10 1 2 56.3
rmftsa_sleepdata_2 1024 0 1 2 2 50.29
robot-failures-lp1_1 88 0 90 1 4 38.64
robot-failures-lp2_1 47 0 90 1 5 42.55
robot-failures-lp3_1 47 0 90 1 4 42.55
robot-failures-lp4_1 117 0 90 1 3 61.54
robot-failures-lp5_1 164 0 90 1 5 28.66
sa-heart_1 462 0 8 2 2 65.37
schizo_1 340 834 12 3 2 52.06
schlvote_2 38 0 4 2 2 73.68
segment_1 2310 0 19 1 7 14.29
segment_2 2310 0 19 1 2 85.71
semeion_1 1593 0 256 1 10 10.17
sensory_2 576 0 0 12 2 58.51
servo_1 167 0 0 5 2 77.25
shuttle-landing-control_1 15 26 0 7 2 93.33
sleep_3 62 8 7 1 2 53.23
sleuth_case1102_2 34 0 5 4 2 55.88
sleuth_case1201_2 50 0 6 2 2 52
sleuth_case1202_2 93 0 4 3 2 61.29
sleuth_case2002_2 147 0 2 5 2 53.06
sleuth_ex1221_2 42 0 8 3 2 54.76
sleuth_ex1605_2 62 0 5 1 2 50
sleuth_ex1714_2 47 0 7 1 2 57.45
sleuth_ex2015_2 60 0 6 2 2 55
sleuth_ex2016_2 87 0 8 3 2 51.72
socmob_2 1156 0 1 5 2 77.85
solar-flare_1 323 0 0 13 2 97.83
solar-flare_2 1066 0 0 13 3 99.53
sonar_1 208 0 60 1 2 53.37
soybean_1 683 2337 0 36 19 13.47
soybean_2 683 2337 0 36 2 86.53
space_ga_2 3107 0 6 1 2 50.4
spambase_1 4601 0 57 1 2 60.6
SPECTF_2 267 0 44 1 2 79.4
spectrometer_2 531 0 100 3 2 89.64
SPECT_1 267 0 0 23 2 58.8
splice_1 3190 0 0 62 3 51.88
splice_2 3190 0 0 62 2 51.88
sponge_1 76 22 0 46 3 92.11
sponge_2 76 22 0 46 2 92.11
squash-stored_1 52 7 21 4 3 44.23
squash-stored_2 52 7 21 4 2 55.77
squash-unstored_1 52 39 20 4 3 46.15
squash-unstored_2 52 39 20 4 2 53.85
steel-plates-fault_1 1941 0 33 1 2 65.33
stock_2 950 0 9 1 2 51.37
strikes_2 625 0 6 1 2 50.4
synthetic_control_1 600 0 60 2 6 16.67
tae_1 151 0 3 3 3 34.44
tae_2 151 0 3 3 2 65.56
teachingAssistant_1 151 0 2 5 3 34.44
tecator_2 240 0 124 1 2 57.5
thoracic-surgery_1 470 0 3 14 2 85.11
thyroid-ann_1 3772 0 21 1 3 92.47
tic-tac-toe_1 958 0 0 10 2 65.34
trains_1 10 51 0 33 2 50
transplant_2 131 0 3 1 2 63.36
triazines_2 186 0 60 1 2 58.6
user-knowledge_1 403 0 5 1 5 32.01
usp05-ft_1 76 37 8 7 6 77.63
usp05_1 203 0 3 14 11 55.17
vehicle_1 846 0 18 1 4 25.77
vehicle_2 846 0 18 1 2 74.23
vertebra-column_1 310 0 6 1 3 48.39
vertebra-column_2 310 0 6 1 2 67.74
veteran_2 137 0 3 5 2 68.61
vineyard_2 52 0 3 1 2 53.85
vinnie_2 380 0 2 1 2 51.32
visualizing_environmental_2 111 0 3 1 2 52.25
visualizing_ethanol_2 88 0 2 1 2 51.14
visualizing_galaxy_2 323 0 4 1 2 54.18
visualizing_hamster_2 73 0 5 1 2 54.79
visualizing_livestock_2 130 0 0 3 2 80.77
visualizing_slope_2 44 0 3 1 2 61.36
visualizing_soil_2 8641 0 3 2 2 55.01
volcanoes-a1_1 3252 0 3 1 5 90.77
volcanoes-a2_1 1623 0 3 1 5 90.63
volcanoes-a3_1 1521 0 3 1 5 90.01
volcanoes-a4_1 1515 0 3 1 5 90.1
volcanoes-b1_1 10176 0 3 1 5 96.22
volcanoes-b2_1 10668 0 3 1 5 96.41
volcanoes-b3_1 10386 0 3 1 5 96.34
volcanoes-b4_1 10190 0 3 1 5 96.22
volcanoes-b5_1 9989 0 3 1 5 96.1
volcanoes-b6_1 10130 0 3 1 5 96.21
volcanoes-c1_1 28626 0 3 1 5 97.45
volcanoes-d1_1 8753 0 3 1 5 94.42
volcanoes-d2_1 9172 0 3 1 5 94.53
volcanoes-d3_1 9285 0 3 1 5 94.46
volcanoes-d4_1 8654 0 3 1 5 94.33
volcanoes-e1_1 1183 0 3 1 5 91.55
volcanoes-e2_1 1080 0 3 1 5 91.11
volcanoes-e3_1 1277 0 3 1 5 91.62
volcanoes-e4_1 1252 0 3 1 5 91.37
volcanoes-e5_1 1112 0 3 1 5 90.83
vote_1 435 392 0 17 2 61.38
vowel_2 990 0 10 3 11 9.09
vowel_3 990 0 10 4 2 90.91
wall-robot-navigation_1 5456 0 24 1 4 40.41
wall-robot-navigation_2 5456 0 2 1 4 40.41
wall-robot-navigation_3 5456 0 4 1 4 40.41
water-treatment_2 527 560 21 18 2 84.82
wdbc_1 569 0 30 1 2 62.74
white-clover_1 63 0 27 5 4 60.32
white-clover_2 63 0 27 5 2 60.32
wholesale-customers_1 440 0 7 2 3 71.82
wilt_1 4839 0 5 1 2 94.61
wind_2 6574 0 14 1 2 53.26
wind_correlations_2 45 0 46 1 2 51.11
wine-quality-white_1 4898 0 11 1 7 44.88
wine_2 178 0 13 1 2 60.11
wisconsin_2 194 0 32 1 2 53.61
witmer_census_1980_2 50 0 4 2 2 52
yeast_1 1484 0 8 1 10 31.2
zoo_1 101 0 1 17 7 40.59
zoo_2 101 0 1 17 2 59.41