Data
arcene

arcene

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

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0 missing
V2319numeric6 unique values
0 missing
V2575numeric64 unique values
0 missing
V2831numeric82 unique values
0 missing
V3087numeric52 unique values
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V3343numeric15 unique values
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V3599numeric82 unique values
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V3855numeric60 unique values
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V4111numeric42 unique values
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V4623numeric13 unique values
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V6159numeric34 unique values
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V6415numeric18 unique values
0 missing
V6671numeric31 unique values
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V6927numeric5 unique values
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V7439numeric41 unique values
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V7695numeric44 unique values
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V7951numeric41 unique values
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V8463numeric13 unique values
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V8719numeric64 unique values
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V8975numeric15 unique values
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V9231numeric85 unique values
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V9487numeric20 unique values
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V9743numeric60 unique values
0 missing
V9999numeric60 unique values
0 missing
V16numeric55 unique values
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V784numeric37 unique values
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V1040numeric15 unique values
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V1808numeric78 unique values
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V2064numeric29 unique values
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V2576numeric90 unique values
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V2832numeric67 unique values
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V3088numeric9 unique values
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V3344numeric21 unique values
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V3600numeric76 unique values
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V3856numeric7 unique values
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V4112numeric54 unique values
0 missing
V4368numeric91 unique values
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V4624numeric45 unique values
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V4880numeric37 unique values
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V5136numeric58 unique values
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V5392numeric53 unique values
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V5648numeric28 unique values
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V5904numeric41 unique values
0 missing
V6160numeric43 unique values
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V6416numeric23 unique values
0 missing
V6672numeric16 unique values
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V6928numeric52 unique values
0 missing
V7184numeric63 unique values
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V7440numeric38 unique values
0 missing
V7696numeric19 unique values
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V7952numeric54 unique values
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V8208numeric62 unique values
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V8464numeric68 unique values
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V8720numeric26 unique values
0 missing
V8976numeric21 unique values
0 missing
V9232numeric54 unique values
0 missing
V9488numeric62 unique values
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V9744numeric88 unique values
0 missing
V10000numeric86 unique values
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V17numeric23 unique values
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V273numeric69 unique values
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V529numeric25 unique values
0 missing
V785numeric31 unique values
0 missing
V1041numeric7 unique values
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V1297numeric59 unique values
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V1553numeric35 unique values
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V1809numeric61 unique values
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V2065numeric32 unique values
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V2321numeric28 unique values
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V2833numeric39 unique values
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V3089numeric17 unique values
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V3345numeric26 unique values
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V3601numeric30 unique values
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V3857numeric32 unique values
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V4625numeric90 unique values
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V4881numeric29 unique values
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V5649numeric64 unique values
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V6161numeric48 unique values
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V6417numeric30 unique values
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V6673numeric24 unique values
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V6929numeric48 unique values
0 missing
V7185numeric84 unique values
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V7441numeric82 unique values
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V7697numeric51 unique values
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V7953numeric36 unique values
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V8209numeric63 unique values
0 missing
V8465numeric66 unique values
0 missing
V8721numeric82 unique values
0 missing
V8977numeric88 unique values
0 missing
V9233numeric61 unique values
0 missing
V9489numeric51 unique values
0 missing
V9745numeric15 unique values
0 missing
V18numeric3 unique values
0 missing
V274numeric42 unique values
0 missing
V530numeric88 unique values
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V786numeric15 unique values
0 missing
V1042numeric20 unique values
0 missing
V1298numeric48 unique values
0 missing
V1554numeric11 unique values
0 missing
V1810numeric54 unique values
0 missing
V2066numeric41 unique values
0 missing
V2322numeric29 unique values
0 missing
V2578numeric18 unique values
0 missing
V2834numeric21 unique values
0 missing
V3090numeric63 unique values
0 missing
V3346numeric86 unique values
0 missing
V3602numeric58 unique values
0 missing
V3858numeric64 unique values
0 missing
V4114numeric57 unique values
0 missing
V4370numeric64 unique values
0 missing
V4626numeric47 unique values
0 missing
V4882numeric85 unique values
0 missing
V5138numeric3 unique values
0 missing
V5394numeric12 unique values
0 missing
V5650numeric18 unique values
0 missing
V5906numeric18 unique values
0 missing
V6162numeric52 unique values
0 missing
V6418numeric19 unique values
0 missing
V6674numeric39 unique values
0 missing
V6930numeric8 unique values
0 missing
V7186numeric45 unique values
0 missing
V7442numeric66 unique values
0 missing
V7698numeric61 unique values
0 missing
V7954numeric86 unique values
0 missing
V8210numeric22 unique values
0 missing
V8466numeric25 unique values
0 missing
V8722numeric95 unique values
0 missing
V8978numeric39 unique values
0 missing
V9234numeric51 unique values
0 missing
V9490numeric62 unique values
0 missing
V9746numeric15 unique values
0 missing
V19numeric83 unique values
0 missing
V275numeric52 unique values
0 missing
V531numeric7 unique values
0 missing
V787numeric35 unique values
0 missing
V1043numeric75 unique values
0 missing
V1299numeric39 unique values
0 missing
V1555numeric57 unique values
0 missing
V1811numeric30 unique values
0 missing
V2067numeric94 unique values
0 missing
V2323numeric35 unique values
0 missing
V2579numeric9 unique values
0 missing
V2835numeric27 unique values
0 missing
V3091numeric89 unique values
0 missing
V3347numeric87 unique values
0 missing
V3603numeric30 unique values
0 missing
V3859numeric21 unique values
0 missing
V4115numeric61 unique values
0 missing
V4371numeric53 unique values
0 missing
V4627numeric55 unique values
0 missing
V4883numeric23 unique values
0 missing
V5139numeric8 unique values
0 missing
V5395numeric56 unique values
0 missing
V5651numeric25 unique values
0 missing
V5907numeric64 unique values
0 missing
V6163numeric55 unique values
0 missing
V6419numeric42 unique values
0 missing
V6675numeric57 unique values
0 missing
V6931numeric55 unique values
0 missing
V7187numeric58 unique values
0 missing
V7443numeric57 unique values
0 missing
V7699numeric41 unique values
0 missing
V7955numeric78 unique values
0 missing
V8211numeric7 unique values
0 missing
V8467numeric39 unique values
0 missing
V8723numeric84 unique values
0 missing
V8979numeric5 unique values
0 missing
V9235numeric82 unique values
0 missing
V9491numeric29 unique values
0 missing
V9747numeric56 unique values
0 missing
V20numeric23 unique values
0 missing
V276numeric49 unique values
0 missing
V532numeric57 unique values
0 missing
V788numeric63 unique values
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V1044numeric16 unique values
0 missing
V1300numeric23 unique values
0 missing
V1556numeric88 unique values
0 missing
V1812numeric64 unique values
0 missing
V2068numeric5 unique values
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V2324numeric40 unique values
0 missing
V2580numeric91 unique values
0 missing
V2836numeric35 unique values
0 missing
V3092numeric36 unique values
0 missing
V3348numeric67 unique values
0 missing
V3604numeric60 unique values
0 missing
V3860numeric52 unique values
0 missing
V4116numeric69 unique values
0 missing
V4372numeric62 unique values
0 missing
V4628numeric23 unique values
0 missing
V4884numeric76 unique values
0 missing
V5140numeric67 unique values
0 missing
V5396numeric17 unique values
0 missing
V5652numeric81 unique values
0 missing
V5908numeric44 unique values
0 missing
V6164numeric37 unique values
0 missing
V6420numeric69 unique values
0 missing
V6676numeric8 unique values
0 missing
V6932numeric26 unique values
0 missing
V7188numeric94 unique values
0 missing
V7444numeric87 unique values
0 missing
V7700numeric74 unique values
0 missing
V7956numeric29 unique values
0 missing
V8212numeric7 unique values
0 missing
V8468numeric46 unique values
0 missing
V8724numeric55 unique values
0 missing
V8980numeric39 unique values
0 missing
V9236numeric91 unique values
0 missing
V9492numeric67 unique values
0 missing
V9748numeric12 unique values
0 missing
V21numeric20 unique values
0 missing
V277numeric76 unique values
0 missing
V533numeric35 unique values
0 missing
V789numeric10 unique values
0 missing
V1045numeric41 unique values
0 missing
V1301numeric79 unique values
0 missing
V1557numeric14 unique values
0 missing
V1813numeric68 unique values
0 missing
V2069numeric58 unique values
0 missing
V2325numeric66 unique values
0 missing
V2581numeric37 unique values
0 missing
V2837numeric84 unique values
0 missing
V3093numeric13 unique values
0 missing
V3349numeric31 unique values
0 missing
V3605numeric64 unique values
0 missing
V3861numeric56 unique values
0 missing
V4117numeric69 unique values
0 missing
V4373numeric32 unique values
0 missing
V4629numeric67 unique values
0 missing
V4885numeric24 unique values
0 missing
V5141numeric9 unique values
0 missing
V5397numeric8 unique values
0 missing
V5653numeric81 unique values
0 missing
V5909numeric42 unique values
0 missing
V6165numeric16 unique values
0 missing
V6421numeric17 unique values
0 missing
V6677numeric47 unique values
0 missing
V6933numeric88 unique values
0 missing
V7189numeric60 unique values
0 missing
V7445numeric63 unique values
0 missing
V7701numeric55 unique values
0 missing
V7957numeric3 unique values
0 missing
V8213numeric84 unique values
0 missing
V8469numeric53 unique values
0 missing
V8725numeric70 unique values
0 missing
V8981numeric74 unique values
0 missing
V9237numeric56 unique values
0 missing
V9493numeric82 unique values
0 missing
V9749numeric23 unique values
0 missing
V22numeric35 unique values
0 missing
V278numeric2 unique values
0 missing
V534numeric59 unique values
0 missing
V790numeric47 unique values
0 missing
V1046numeric21 unique values
0 missing
V1302numeric2 unique values
0 missing
V1558numeric38 unique values
0 missing
V1814numeric55 unique values
0 missing
V2070numeric62 unique values
0 missing
V2326numeric34 unique values
0 missing
V2582numeric23 unique values
0 missing
V2838numeric50 unique values
0 missing
V3094numeric34 unique values
0 missing
V3350numeric67 unique values
0 missing
V3606numeric15 unique values
0 missing
V3862numeric24 unique values
0 missing
V4118numeric32 unique values
0 missing
V4374numeric86 unique values
0 missing
V4630numeric19 unique values
0 missing
V4886numeric86 unique values
0 missing
V5142numeric50 unique values
0 missing
V5398numeric6 unique values
0 missing
V5654numeric12 unique values
0 missing
V5910numeric48 unique values
0 missing
V6166numeric51 unique values
0 missing
V6422numeric31 unique values
0 missing
V6678numeric9 unique values
0 missing
V6934numeric79 unique values
0 missing
V7190numeric30 unique values
0 missing
V7446numeric86 unique values
0 missing
V7702numeric54 unique values
0 missing
V7958numeric42 unique values
0 missing
V8214numeric24 unique values
0 missing
V8470numeric8 unique values
0 missing
V8726numeric35 unique values
0 missing
V8982numeric8 unique values
0 missing
V9238numeric61 unique values
0 missing
V9494numeric54 unique values
0 missing
V9750numeric88 unique values
0 missing
V23numeric30 unique values
0 missing
V279numeric47 unique values
0 missing
V535numeric17 unique values
0 missing
V791numeric37 unique values
0 missing
V1047numeric66 unique values
0 missing
V1303numeric5 unique values
0 missing
V1559numeric52 unique values
0 missing
V1815numeric57 unique values
0 missing
V2071numeric87 unique values
0 missing
V2327numeric26 unique values
0 missing
V2583numeric86 unique values
0 missing
V2839numeric20 unique values
0 missing
V3095numeric19 unique values
0 missing
V3351numeric31 unique values
0 missing
V3607numeric27 unique values
0 missing
V3863numeric60 unique values
0 missing
V4119numeric35 unique values
0 missing
V4375numeric61 unique values
0 missing
V4631numeric55 unique values
0 missing
V4887numeric53 unique values
0 missing
V5143numeric59 unique values
0 missing
V5399numeric43 unique values
0 missing
V5655numeric51 unique values
0 missing
V5911numeric45 unique values
0 missing
V6167numeric92 unique values
0 missing
V6423numeric30 unique values
0 missing
V6679numeric40 unique values
0 missing
V6935numeric28 unique values
0 missing
V7191numeric70 unique values
0 missing
V7447numeric90 unique values
0 missing
V7703numeric24 unique values
0 missing
V7959numeric4 unique values
0 missing
V8215numeric24 unique values
0 missing
V8471numeric45 unique values
0 missing
V8727numeric32 unique values
0 missing
V8983numeric60 unique values
0 missing
V9239numeric47 unique values
0 missing
V9495numeric17 unique values
0 missing
V9751numeric52 unique values
0 missing
V24numeric46 unique values
0 missing
V280numeric48 unique values
0 missing
V536numeric13 unique values
0 missing
V792numeric7 unique values
0 missing
V1048numeric2 unique values
0 missing
V1304numeric51 unique values
0 missing
V1560numeric55 unique values
0 missing
V1816numeric50 unique values
0 missing
V2072numeric92 unique values
0 missing
V2328numeric19 unique values
0 missing
V2584numeric1 unique values
0 missing
V2840numeric43 unique values
0 missing
V3096numeric17 unique values
0 missing
V3352numeric37 unique values
0 missing
V3608numeric31 unique values
0 missing
V3864numeric49 unique values
0 missing
V4120numeric54 unique values
0 missing
V4376numeric40 unique values
0 missing
V4632numeric79 unique values
0 missing
V4888numeric10 unique values
0 missing
V5144numeric40 unique values
0 missing
V5400numeric23 unique values
0 missing
V5656numeric3 unique values
0 missing
V5912numeric4 unique values
0 missing
V6168numeric6 unique values
0 missing
V6424numeric26 unique values
0 missing
V6680numeric83 unique values
0 missing
V6936numeric62 unique values
0 missing
V7192numeric57 unique values
0 missing
V7448numeric2 unique values
0 missing
V7704numeric20 unique values
0 missing
V7960numeric36 unique values
0 missing
V8216numeric23 unique values
0 missing
V8472numeric60 unique values
0 missing
V8728numeric59 unique values
0 missing
V8984numeric41 unique values
0 missing
V9240numeric82 unique values
0 missing
V9496numeric21 unique values
0 missing
V9752numeric24 unique values
0 missing
V25numeric64 unique values
0 missing
V281numeric87 unique values
0 missing
V537numeric53 unique values
0 missing
V793numeric6 unique values
0 missing
V1049numeric9 unique values
0 missing
V1305numeric23 unique values
0 missing
V1561numeric55 unique values
0 missing
V1817numeric46 unique values
0 missing

62 properties

100
Number of instances (rows) of the dataset.
10001
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.
10000
Number of numeric attributes.
1
Number of nominal attributes.
100.01
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
2.54
Second quartile (Median) of kurtosis 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.
2.18
Mean skewness among attributes of the numeric type.
30.83
Second quartile (Median) of means among attributes of the numeric type.
56
Percentage of instances belonging to the most frequent class.
59.36
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
56
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.67
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.78
Minimum kurtosis among attributes of the numeric type.
0.01
Percentage of binary attributes.
41.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
100
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
553.59
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
10.73
Third quartile of kurtosis 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.
99.99
Percentage of numeric attributes.
81.71
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
-1.65
Minimum skewness among attributes of the numeric type.
0.01
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
10
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.05
Third quartile of skewness among attributes of the numeric type.
317.37
Maximum standard deviation of attributes of the numeric type.
44
Percentage of instances belonging to the least frequent class.
-0.44
First quartile of kurtosis among attributes of the numeric type.
82.19
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
44
Number of instances belonging to the least frequent class.
10.17
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.
9.66
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
70.73
Mean of means among attributes of the numeric type.
0.71
First quartile of skewness among attributes of the numeric type.
0.39
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
21.88
First quartile of standard deviation of attributes of the numeric type.
0.99
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.
Second quartile (Median) of entropy among attributes.

5 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - 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: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
Define a new task