Data
BNG(vehicle)

BNG(vehicle)

active ARFF Publicly available Visibility: public Uploaded 29-04-2014 by Jan van Rijn
0 likes downloaded by 3 people , 3 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

19 features

Class (target)nominal4 unique values
0 missing
COMPACTNESSnumeric981472 unique values
0 missing
CIRCULARITYnumeric975090 unique values
0 missing
DISTANCE_CIRCULARITYnumeric989524 unique values
0 missing
RADIUS_RATIOnumeric995580 unique values
0 missing
PR.AXIS_ASPECT_RATIOnumeric973700 unique values
0 missing
MAX.LENGTH_ASPECT_RATIOnumeric624816 unique values
0 missing
SCATTER_RATIOnumeric993561 unique values
0 missing
ELONGATEDNESSnumeric975101 unique values
0 missing
PR.AXIS_RECTANGULARITYnumeric668739 unique values
0 missing
MAX.LENGTH_RECTANGULARITYnumeric989050 unique values
0 missing
SCALED_VARIANCE_MAJORnumeric993030 unique values
0 missing
SCALED_VARIANCE_MINORnumeric998508 unique values
0 missing
SCALED_RADIUS_OF_GYRATIONnumeric995243 unique values
0 missing
SKEWNESS_ABOUT_MAJORnumeric972577 unique values
0 missing
SKEWNESS_ABOUT_MINORnumeric963671 unique values
0 missing
KURTOSIS_ABOUT_MAJORnumeric981599 unique values
0 missing
KURTOSIS_ABOUT_MINORnumeric974847 unique values
0 missing
HOLLOWS_RATIOnumeric978199 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
19
Number of attributes (columns) of the dataset.
4
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.
18
Number of numeric attributes.
1
Number of nominal attributes.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
4
Average number of distinct values among the attributes of the nominal type.
0.25
First quartile of skewness among attributes of the numeric type.
0.63
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.61
Mean skewness among attributes of the numeric type.
6.1
First quartile of standard deviation of attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.35
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
22.33
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.36
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
25.75
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.58
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.63
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2
Entropy of the target attribute values.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
257546
Number of instances belonging to the most frequent class.
-1.03
Minimum kurtosis among attributes of the numeric type.
87.84
Second quartile (Median) of means among attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
6.37
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.62
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
8.63
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.49
Second quartile (Median) of skewness among attributes of the numeric type.
0.63
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
434.95
Maximum of means among attributes of the numeric type.
4
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
8.01
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-0.28
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.34
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
4
The maximum number of distinct values among attributes of the nominal type.
2.51
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
-0.22
Third quartile of kurtosis among attributes of the numeric type.
0.25
Average class difference between consecutive instances.
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.21
Maximum skewness among attributes of the numeric type.
23.56
Percentage of instances belonging to the least frequent class.
94.74
Percentage of numeric attributes.
177.56
Third quartile of means among attributes of the numeric type.
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
172.05
Maximum standard deviation of attributes of the numeric type.
235618
Number of instances belonging to the least frequent class.
5.26
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.34
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.81
Third quartile of skewness among attributes of the numeric type.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.31
Mean kurtosis among attributes of the numeric type.
0.52
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.72
First quartile of kurtosis among attributes of the numeric type.
30.77
Third quartile of standard deviation of attributes of the numeric type.
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
117.28
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
35.88
First quartile of means among attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.35
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.34
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

8 tasks

19 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - 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 - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
285 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
Define a new task