Data
Agrawal1

Agrawal1

active ARFF Publicly available Visibility: public Uploaded 13-02-2015 by Jan van Rijn
0 likes downloaded by 5 people , 5 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

10 features

class (target)nominal2 unique values
0 missing
salarynumeric974969 unique values
0 missing
commissionnumeric412917 unique values
0 missing
agenumeric61 unique values
0 missing
elevelnominal5 unique values
0 missing
carnominal20 unique values
0 missing
zipcodenominal9 unique values
0 missing
hvaluenumeric113321 unique values
0 missing
hyearsnumeric30 unique values
0 missing
loannumeric974942 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
10
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.
6
Number of numeric attributes.
4
Number of nominal attributes.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
144574.13
Maximum standard deviation of attributes of the numeric type.
32.8
Percentage of instances belonging to the least frequent class.
60
Percentage of numeric attributes.
160513.49
Third quartile of means among attributes of the numeric type.
0.95
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
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.27
Average entropy of the attributes.
327955
Number of instances belonging to the least frequent class.
40
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.05
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
0.84
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.33
Mean kurtosis among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.32
First quartile of entropy among attributes.
0.24
Third quartile of skewness among attributes of the numeric type.
0.89
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
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
80627.3
Mean of means among attributes of the numeric type.
0.11
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.2
First quartile of kurtosis among attributes of the numeric type.
64354.91
Third quartile of standard deviation of attributes of the numeric type.
0.95
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
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0
Average mutual information between the nominal attributes and the target attribute.
0.72
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
41.38
First quartile of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.05
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
0.84
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
577673.11
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.89
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
7.87
Standard deviation of the number of distinct values among attributes of the nominal type.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
9
Average number of distinct values among the attributes of the nominal type.
-0.93
First quartile of skewness among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.95
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.46
Mean skewness among attributes of the numeric type.
15.38
First quartile of standard deviation of attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.05
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
0.15
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
67.2
Percentage of instances belonging to the most frequent class.
36875.44
Mean standard deviation of attributes of the numeric type.
3.17
Second quartile (Median) of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.89
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
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
672045
Number of instances belonging to the most frequent class.
2.32
Minimal entropy among attributes.
-1.19
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.91
Entropy of the target attribute values.
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
4.32
Maximum entropy among attributes.
-1.2
Minimum kurtosis among attributes of the numeric type.
51473.3
Second quartile (Median) of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.33
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
13.33
Maximum kurtosis among attributes of the numeric type.
15.51
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
250100.57
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
-0
Second quartile (Median) of skewness among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Number of attributes divided by the number of instances.
0
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
10
Percentage of binary attributes.
19518.53
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
161196.71
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
20
The maximum number of distinct values among attributes of the nominal type.
-3.71
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
4.32
Third quartile of entropy among attributes.
0.84
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.97
Maximum skewness among attributes of the numeric type.
8.66
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
2.9
Third quartile of kurtosis among attributes of the numeric type.
0.56
Average class difference between consecutive instances.

12 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - 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
311 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task