Data
BNG(trains)

BNG(trains)

active ARFF Publicly available Visibility: public Uploaded 09-04-2014 by Jan van Rijn
0 likes downloaded by 4 people , 7 total downloads 0 issues 0 downvotes
  • artificial BNG study_16 study_69
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

33 features

class (target)nominal2 unique values
0 missing
Number_of_carsnominal3 unique values
0 missing
Number_of_different_loadsnominal4 unique values
0 missing
num_wheels_2nominal2 unique values
0 missing
length_2nominal2 unique values
0 missing
shape_2nominal5 unique values
0 missing
num_loads_2nominal2 unique values
0 missing
load_shape_2nominal3 unique values
0 missing
num_wheels_3nominal2 unique values
0 missing
length_3nominal2 unique values
0 missing
shape_3nominal8 unique values
0 missing
num_loads_3nominal2 unique values
0 missing
load_shape_3nominal3 unique values
0 missing
num_wheels_4nominal2 unique values
0 missing
length_4nominal2 unique values
0 missing
shape_4nominal4 unique values
0 missing
num_loads_4nominal3 unique values
0 missing
load_shape_4nominal4 unique values
0 missing
num_wheels_5nominal1 unique values
0 missing
length_5nominal1 unique values
0 missing
shape_5nominal2 unique values
0 missing
num_loads_5nominal1 unique values
0 missing
load_shape_5nominal2 unique values
0 missing
Rectangle_next_to_rectanglenominal2 unique values
0 missing
Rectangle_next_to_trianglenominal2 unique values
0 missing
Rectangle_next_to_hexagonnominal1 unique values
0 missing
Rectangle_next_to_circlenominal2 unique values
0 missing
Triangle_next_to_trianglenominal2 unique values
0 missing
Triangle_next_to_hexagonnominal2 unique values
0 missing
Triangle_next_to_circlenominal2 unique values
0 missing
Hexagon_next_to_hexagonnominal1 unique values
0 missing
Hexagon_next_to_circlenominal2 unique values
0 missing
Circle_next_to_circlenominal1 unique values
0 missing

19 properties

1000000
Number of instances (rows) of the dataset.
33
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.
0
Number of numeric attributes.
33
Number of nominal attributes.
0
Percentage of instances having missing values.
0.5
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
0
Percentage of numeric attributes.
50.11
Percentage of instances belonging to the most frequent class.
100
Percentage of nominal attributes.
501119
Number of instances belonging to the most frequent class.
49.89
Percentage of instances belonging to the least frequent class.
498881
Number of instances belonging to the least frequent class.
18
Number of binary attributes.
54.55
Percentage of binary attributes.

26 tasks

21 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
312 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
Define a new task