Data
BNG(dermatology,nominal,1000000)

BNG(dermatology,nominal,1000000)

active ARFF Publicly available Visibility: public Uploaded 08-04-2014 by Jan van Rijn
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35 features

class (target)nominal6 unique values
0 missing
erythemanominal4 unique values
0 missing
scalingnominal4 unique values
0 missing
definite_bordersnominal4 unique values
0 missing
itchingnominal4 unique values
0 missing
koebner_phenomenonnominal4 unique values
0 missing
polygonal_papulesnominal4 unique values
0 missing
follicular_papulesnominal4 unique values
0 missing
oral_mucosal_involvementnominal4 unique values
0 missing
knee_and_elbow_involvementnominal4 unique values
0 missing
scalp_involvementnominal4 unique values
0 missing
family_historynominal2 unique values
0 missing
melanin_incontinencenominal4 unique values
0 missing
eosinophils_in_the_infiltratenominal3 unique values
0 missing
PNL_infiltratenominal4 unique values
0 missing
fibrosis_of_the_papillary_dermisnominal4 unique values
0 missing
exocytosisnominal4 unique values
0 missing
acanthosisnominal4 unique values
0 missing
hyperkeratosisnominal4 unique values
0 missing
parakeratosisnominal4 unique values
0 missing
clubbing_of_the_rete_ridgesnominal4 unique values
0 missing
elongation_of_the_rete_ridgesnominal4 unique values
0 missing
thinning_of_the_suprapapillary_epidermisnominal4 unique values
0 missing
spongiform_pustulenominal4 unique values
0 missing
munro_microabcessnominal4 unique values
0 missing
focal_hypergranulosisnominal4 unique values
0 missing
disappearance_of_the_granular_layernominal4 unique values
0 missing
vacuolisation_and_damage_of_basal_layernominal4 unique values
0 missing
spongiosisnominal4 unique values
0 missing
saw-tooth_appearance_of_retesnominal4 unique values
0 missing
follicular_horn_plugnominal4 unique values
0 missing
perifollicular_parakeratosisnominal4 unique values
0 missing
inflammatory_monoluclear_inflitratenominal4 unique values
0 missing
band-like_infiltratenominal4 unique values
0 missing
Agenominal3 unique values
0 missing
Show all 35 features

19 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
35
Number of attributes (columns) of the dataset.
NumberOfClasses
6
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
0
Number of numeric attributes.
NumberOfSymbolicFeatures
35
Number of nominal attributes.
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2.86
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
0.2
Average class difference between consecutive instances.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
Dimensionality
0
Number of attributes divided by the number of instances.
MajorityClassPercentage
30.46
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
MajorityClassSize
304611
Number of instances belonging to the most frequent class.
MinorityClassPercentage
5.49
Percentage of instances belonging to the least frequent class.
MinorityClassSize
54922
Number of instances belonging to the least frequent class.
Show all 19 properties

27 tasks

Supervised Classification on BNG(dermatology,nominal,1000000)
19 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on BNG(dermatology,nominal,1000000)
47 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(dermatology,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
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