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guillermo

guillermo

active ARFF Publicly available Visibility: public Uploaded 16-08-2018 by Janek Thomas
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The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The data are provided as preprocessed matrices, so that participants can focus on classification, although participants are welcome to use additional feature extraction procedures (as long as they do not violate any rule of the challenge). All problems are binary classification problems and are assessed with the normalized Area Under the ROC Curve (AUC) metric (i.e. 2*AUC-1). The identity of the datasets and the type of data is concealed, though its structure is revealed. The final score in phase 2 will be the average of rankings on all testing datasets, a ranking will be generated from such results, and winners will be determined according to such ranking. The tasks are constrained by a time budget. The Codalab platform provides computational resources shared by all participants. Each code submission will be exceuted in a compute worker with the following characteristics: 2Cores / 8G Memory / 40G SSD with Ubuntu OS. To ensure the fairness of the evaluation, when a code submission is evaluated, its execution time is limited in time. http://automl.chalearn.org/data

4297 features

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0 missing
V2594numeric580 unique values
0 missing
V2850numeric1075 unique values
0 missing
V3106numeric610 unique values
0 missing
V3362numeric742 unique values
0 missing
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0 missing
V3874numeric1432 unique values
0 missing
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0 missing
V35numeric1317 unique values
0 missing
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0 missing
V547numeric418 unique values
0 missing
V803numeric770 unique values
0 missing
V1059numeric668 unique values
0 missing
V1315numeric1355 unique values
0 missing
V1571numeric308 unique values
0 missing
V1827numeric189 unique values
0 missing
V2083numeric474 unique values
0 missing
V2339numeric949 unique values
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V2595numeric826 unique values
0 missing
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0 missing
V3107numeric803 unique values
0 missing
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0 missing
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0 missing
V3875numeric1021 unique values
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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V1573numeric1071 unique values
0 missing
V1829numeric1090 unique values
0 missing
V2085numeric509 unique values
0 missing
V2341numeric921 unique values
0 missing
V2597numeric1199 unique values
0 missing
V2853numeric962 unique values
0 missing
V3109numeric605 unique values
0 missing
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0 missing
V3621numeric521 unique values
0 missing
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0 missing
V38numeric1220 unique values
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0 missing
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0 missing
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V1574numeric1062 unique values
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V2854numeric853 unique values
0 missing
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0 missing
V3366numeric1000 unique values
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V3622numeric1358 unique values
0 missing
V3878numeric896 unique values
0 missing
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0 missing
V39numeric386 unique values
0 missing
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0 missing
V551numeric759 unique values
0 missing
V807numeric1464 unique values
0 missing
V1063numeric911 unique values
0 missing
V1319numeric857 unique values
0 missing
V1575numeric777 unique values
0 missing
V1831numeric310 unique values
0 missing
V2087numeric604 unique values
0 missing
V2343numeric418 unique values
0 missing
V2599numeric634 unique values
0 missing
V2855numeric323 unique values
0 missing
V3111numeric1272 unique values
0 missing
V3367numeric1265 unique values
0 missing
V3623numeric1059 unique values
0 missing
V3879numeric1105 unique values
0 missing
V4135numeric5722 unique values
0 missing
V40numeric1387 unique values
0 missing
V296numeric1195 unique values
0 missing
V552numeric1228 unique values
0 missing
V808numeric916 unique values
0 missing
V1064numeric1035 unique values
0 missing
V1320numeric669 unique values
0 missing
V1576numeric169 unique values
0 missing
V1832numeric1055 unique values
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V2088numeric934 unique values
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V2344numeric1065 unique values
0 missing
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V2856numeric312 unique values
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0 missing
V3368numeric1124 unique values
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V3624numeric1237 unique values
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V3880numeric1096 unique values
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V41numeric859 unique values
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V297numeric899 unique values
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V809numeric1026 unique values
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V1065numeric767 unique values
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V1577numeric519 unique values
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V1833numeric851 unique values
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V2089numeric234 unique values
0 missing
V2345numeric679 unique values
0 missing
V2601numeric597 unique values
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V2857numeric1076 unique values
0 missing
V3113numeric1200 unique values
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V3369numeric1471 unique values
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V3625numeric692 unique values
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0 missing
V4137numeric5703 unique values
0 missing
V42numeric956 unique values
0 missing
V298numeric937 unique values
0 missing
V554numeric304 unique values
0 missing
V810numeric603 unique values
0 missing
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0 missing
V1322numeric926 unique values
0 missing
V1578numeric1296 unique values
0 missing
V1834numeric1331 unique values
0 missing
V2090numeric1307 unique values
0 missing
V2346numeric1151 unique values
0 missing
V2602numeric573 unique values
0 missing
V2858numeric793 unique values
0 missing
V3114numeric909 unique values
0 missing
V3370numeric911 unique values
0 missing
V3626numeric1040 unique values
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V3882numeric1305 unique values
0 missing
V4138numeric5715 unique values
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V43numeric982 unique values
0 missing
V299numeric1074 unique values
0 missing
V555numeric1134 unique values
0 missing
V811numeric928 unique values
0 missing
V1067numeric547 unique values
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V1323numeric811 unique values
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V2347numeric966 unique values
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V2859numeric929 unique values
0 missing
V3115numeric1302 unique values
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V3371numeric994 unique values
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V812numeric806 unique values
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V1068numeric1019 unique values
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V1324numeric844 unique values
0 missing
V1580numeric1125 unique values
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V1836numeric1086 unique values
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V2092numeric903 unique values
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V2348numeric918 unique values
0 missing
V2604numeric573 unique values
0 missing
V2860numeric822 unique values
0 missing
V3116numeric1358 unique values
0 missing
V3372numeric446 unique values
0 missing
V3628numeric323 unique values
0 missing
V3884numeric1 unique values
0 missing
V4140numeric5722 unique values
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V45numeric1206 unique values
0 missing
V301numeric576 unique values
0 missing
V557numeric587 unique values
0 missing
V813numeric173 unique values
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V1069numeric918 unique values
0 missing
V1325numeric196 unique values
0 missing
V1581numeric1153 unique values
0 missing
V1837numeric125 unique values
0 missing
V2093numeric951 unique values
0 missing
V2349numeric1172 unique values
0 missing
V2605numeric457 unique values
0 missing
V2861numeric1330 unique values
0 missing
V3117numeric828 unique values
0 missing
V3373numeric708 unique values
0 missing
V3629numeric940 unique values
0 missing
V3885numeric713 unique values
0 missing
V4141numeric5706 unique values
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V46numeric824 unique values
0 missing
V302numeric796 unique values
0 missing
V558numeric528 unique values
0 missing
V814numeric1237 unique values
0 missing
V1070numeric848 unique values
0 missing
V1326numeric441 unique values
0 missing
V1582numeric793 unique values
0 missing
V1838numeric1294 unique values
0 missing
V2094numeric992 unique values
0 missing
V2350numeric1293 unique values
0 missing
V2606numeric1183 unique values
0 missing
V2862numeric1128 unique values
0 missing
V3118numeric999 unique values
0 missing
V3374numeric955 unique values
0 missing
V3630numeric1018 unique values
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V3886numeric1025 unique values
0 missing
V4142numeric5733 unique values
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V47numeric554 unique values
0 missing
V303numeric1204 unique values
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V559numeric564 unique values
0 missing
V815numeric1343 unique values
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V1071numeric1078 unique values
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V1327numeric713 unique values
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V1583numeric943 unique values
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V1839numeric705 unique values
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V2095numeric1038 unique values
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V2351numeric1262 unique values
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V2607numeric327 unique values
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V2863numeric883 unique values
0 missing
V3119numeric488 unique values
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V3375numeric893 unique values
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V3631numeric667 unique values
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V3887numeric840 unique values
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V4143numeric5673 unique values
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V48numeric1263 unique values
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V304numeric831 unique values
0 missing
V560numeric705 unique values
0 missing
V816numeric754 unique values
0 missing
V1072numeric446 unique values
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V1328numeric1024 unique values
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V1584numeric1178 unique values
0 missing
V1840numeric644 unique values
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V2096numeric1044 unique values
0 missing
V2352numeric1011 unique values
0 missing
V2608numeric815 unique values
0 missing
V2864numeric1138 unique values
0 missing
V3120numeric786 unique values
0 missing
V3376numeric414 unique values
0 missing
V3632numeric700 unique values
0 missing
V3888numeric1313 unique values
0 missing
V4144numeric5731 unique values
0 missing
V49numeric1303 unique values
0 missing
V305numeric1116 unique values
0 missing
V561numeric751 unique values
0 missing
V817numeric476 unique values
0 missing
V1073numeric882 unique values
0 missing
V1329numeric1032 unique values
0 missing
V1585numeric884 unique values
0 missing
V1841numeric438 unique values
0 missing
V2097numeric1012 unique values
0 missing
V2353numeric641 unique values
0 missing
V2609numeric1285 unique values
0 missing
V2865numeric863 unique values
0 missing
V3121numeric1116 unique values
0 missing
V3377numeric749 unique values
0 missing
V3633numeric778 unique values
0 missing
V3889numeric689 unique values
0 missing
V4145numeric5733 unique values
0 missing
V50numeric816 unique values
0 missing
V306numeric993 unique values
0 missing
V562numeric1114 unique values
0 missing
V818numeric974 unique values
0 missing
V1074numeric645 unique values
0 missing
V1330numeric904 unique values
0 missing
V1586numeric852 unique values
0 missing
V1842numeric1073 unique values
0 missing
V2098numeric866 unique values
0 missing
V2354numeric812 unique values
0 missing
V2610numeric1232 unique values
0 missing
V2866numeric597 unique values
0 missing
V3122numeric980 unique values
0 missing
V3378numeric1160 unique values
0 missing
V3634numeric656 unique values
0 missing
V3890numeric762 unique values
0 missing
V4146numeric5735 unique values
0 missing
V51numeric1019 unique values
0 missing
V307numeric953 unique values
0 missing
V563numeric893 unique values
0 missing
V819numeric763 unique values
0 missing
V1075numeric723 unique values
0 missing
V1331numeric975 unique values
0 missing
V1587numeric1015 unique values
0 missing
V1843numeric812 unique values
0 missing
V2099numeric690 unique values
0 missing
V2355numeric200 unique values
0 missing
V2611numeric497 unique values
0 missing
V2867numeric1009 unique values
0 missing
V3123numeric739 unique values
0 missing
V3379numeric161 unique values
0 missing
V3635numeric1268 unique values
0 missing
V3891numeric764 unique values
0 missing
V4147numeric5720 unique values
0 missing
V52numeric1078 unique values
0 missing
V308numeric686 unique values
0 missing
V564numeric752 unique values
0 missing
V820numeric826 unique values
0 missing
V1076numeric1029 unique values
0 missing
V1332numeric1161 unique values
0 missing
V1588numeric649 unique values
0 missing
V1844numeric918 unique values
0 missing
V2100numeric998 unique values
0 missing
V2356numeric1288 unique values
0 missing
V2612numeric477 unique values
0 missing
V2868numeric1006 unique values
0 missing
V3124numeric697 unique values
0 missing
V3380numeric986 unique values
0 missing
V3636numeric794 unique values
0 missing
V3892numeric956 unique values
0 missing
V4148numeric5734 unique values
0 missing
V53numeric736 unique values
0 missing
V309numeric831 unique values
0 missing
V565numeric628 unique values
0 missing
V821numeric741 unique values
0 missing
V1077numeric443 unique values
0 missing
V1333numeric929 unique values
0 missing
V1589numeric1068 unique values
0 missing
V1845numeric774 unique values
0 missing
V2101numeric899 unique values
0 missing
V2357numeric728 unique values
0 missing
V2613numeric851 unique values
0 missing
V2869numeric536 unique values
0 missing
V3125numeric705 unique values
0 missing
V3381numeric818 unique values
0 missing
V3637numeric676 unique values
0 missing
V3893numeric955 unique values
0 missing
V4149numeric5716 unique values
0 missing
V54numeric769 unique values
0 missing
V310numeric872 unique values
0 missing
V566numeric686 unique values
0 missing
V822numeric755 unique values
0 missing
V1078numeric1221 unique values
0 missing
V1334numeric1119 unique values
0 missing
V1590numeric1170 unique values
0 missing
V1846numeric131 unique values
0 missing
V2102numeric1100 unique values
0 missing
V2358numeric259 unique values
0 missing
V2614numeric1007 unique values
0 missing
V2870numeric397 unique values
0 missing
V3126numeric810 unique values
0 missing
V3382numeric1308 unique values
0 missing
V3638numeric246 unique values
0 missing
V3894numeric580 unique values
0 missing
V4150numeric5718 unique values
0 missing
V55numeric950 unique values
0 missing
V311numeric550 unique values
0 missing
V567numeric1035 unique values
0 missing
V823numeric1275 unique values
0 missing
V1079numeric553 unique values
0 missing
V1335numeric885 unique values
0 missing
V1591numeric189 unique values
0 missing
V1847numeric503 unique values
0 missing
V2103numeric1337 unique values
0 missing
V2359numeric893 unique values
0 missing
V2615numeric247 unique values
0 missing
V2871numeric567 unique values
0 missing
V3127numeric735 unique values
0 missing
V3383numeric1330 unique values
0 missing
V3639numeric884 unique values
0 missing
V3895numeric807 unique values
0 missing
V4151numeric5736 unique values
0 missing
V56numeric780 unique values
0 missing
V312numeric1119 unique values
0 missing
V568numeric246 unique values
0 missing
V824numeric1159 unique values
0 missing
V1080numeric937 unique values
0 missing
V1336numeric1187 unique values
0 missing
V1592numeric887 unique values
0 missing
V1848numeric1283 unique values
0 missing
V2104numeric1044 unique values
0 missing
V2360numeric481 unique values
0 missing
V2616numeric845 unique values
0 missing
V2872numeric794 unique values
0 missing
V3128numeric845 unique values
0 missing
V3384numeric833 unique values
0 missing
V3640numeric679 unique values
0 missing
V3896numeric920 unique values
0 missing
V4152numeric5724 unique values
0 missing
V57numeric457 unique values
0 missing
V313numeric595 unique values
0 missing
V569numeric1033 unique values
0 missing
V825numeric1022 unique values
0 missing
V1081numeric661 unique values
0 missing
V1337numeric1351 unique values
0 missing
V1593numeric475 unique values
0 missing
V1849numeric1122 unique values
0 missing
V2105numeric1136 unique values
0 missing
V2361numeric1097 unique values
0 missing
V2617numeric1189 unique values
0 missing
V2873numeric990 unique values
0 missing
V3129numeric930 unique values
0 missing
V3385numeric1246 unique values
0 missing
V3641numeric1033 unique values
0 missing
V3897numeric469 unique values
0 missing
V4153numeric5711 unique values
0 missing
V58numeric811 unique values
0 missing
V314numeric1111 unique values
0 missing
V570numeric1182 unique values
0 missing
V826numeric737 unique values
0 missing
V1082numeric518 unique values
0 missing
V1338numeric971 unique values
0 missing
V1594numeric1045 unique values
0 missing
V1850numeric1131 unique values
0 missing
V2106numeric763 unique values
0 missing
V2362numeric931 unique values
0 missing
V2618numeric640 unique values
0 missing
V2874numeric1372 unique values
0 missing
V3130numeric1138 unique values
0 missing
V3386numeric1041 unique values
0 missing

62 properties

20000
Number of instances (rows) of the dataset.
4297
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
4296
Number of numeric attributes.
1
Number of nominal attributes.
0.02
Percentage of binary attributes.
0.73
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.03
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
2217.78
Maximum kurtosis among attributes of the numeric type.
-0.37
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
20.65
Third quartile of kurtosis among attributes of the numeric type.
3.45
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
99.98
Percentage of numeric attributes.
0.58
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0.02
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-0.68
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
3.93
Third quartile of skewness among attributes of the numeric type.
47.11
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
5.29
First quartile of kurtosis among attributes of the numeric type.
0.91
Third quartile of standard deviation of attributes of the numeric type.
2.59
Maximum standard deviation of attributes of the numeric type.
40.02
Percentage of instances belonging to the least frequent class.
0.22
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
8003
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
20.36
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
2.11
First quartile of skewness among attributes of the numeric type.
0.43
Mean of means among attributes of the numeric type.
0.55
First quartile of standard deviation of attributes of the numeric type.
0.52
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
0.97
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
10.5
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.21
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
0.38
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
3.27
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
59.99
Percentage of instances belonging to the most frequent class.
0.74
Mean standard deviation of attributes of the numeric type.
2.87
Second quartile (Median) of skewness among attributes of the numeric type.
11997
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

7 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_class_complexity - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
Define a new task