Data
LED(50000)

LED(50000)

active ARFF Publicly available Visibility: public Uploaded 10-04-2014 by Jan van Rijn
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  • concept_drift study_16 synthetic
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25 features

class (target)nominal10 unique values
0 missing
att1nominal2 unique values
0 missing
att2nominal2 unique values
0 missing
att3nominal2 unique values
0 missing
att4nominal2 unique values
0 missing
att5nominal2 unique values
0 missing
att6nominal2 unique values
0 missing
att7nominal2 unique values
0 missing
att8nominal2 unique values
0 missing
att9nominal2 unique values
0 missing
att10nominal2 unique values
0 missing
att11nominal2 unique values
0 missing
att12nominal2 unique values
0 missing
att13nominal2 unique values
0 missing
att14nominal2 unique values
0 missing
att15nominal2 unique values
0 missing
att16nominal2 unique values
0 missing
att17nominal2 unique values
0 missing
att18nominal2 unique values
0 missing
att19nominal2 unique values
0 missing
att20nominal2 unique values
0 missing
att21nominal2 unique values
0 missing
att22nominal2 unique values
0 missing
att23nominal2 unique values
0 missing
att24nominal2 unique values
0 missing

19 properties

1000000
Number of instances (rows) of the dataset.
25
Number of attributes (columns) of the dataset.
10
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.
0
Number of numeric attributes.
25
Number of nominal attributes.
0
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
100
Percentage of nominal attributes.
10.08
Percentage of instances belonging to the most frequent class.
100824
Number of instances belonging to the most frequent class.
9.94
Percentage of instances belonging to the least frequent class.
99427
Number of instances belonging to the least frequent class.
24
Number of binary attributes.
96
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.1
Average class difference between consecutive instances.

26 tasks

16 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
1 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - 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: 10-fold Learning 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: 10-fold Learning 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
287 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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