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cpu_act

cpu_act

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others as negative ('N').

22 features

binaryClass (target)nominal2 unique values
0 missing
lreadnumeric235 unique values
0 missing
lwritenumeric189 unique values
0 missing
scallnumeric4115 unique values
0 missing
sreadnumeric794 unique values
0 missing
swritenumeric640 unique values
0 missing
forknumeric228 unique values
0 missing
execnumeric386 unique values
0 missing
rcharnumeric7997 unique values
0 missing
wcharnumeric7939 unique values
0 missing
pgoutnumeric404 unique values
0 missing
ppgoutnumeric774 unique values
0 missing
pgfreenumeric1070 unique values
0 missing
pgscannumeric1202 unique values
0 missing
atchnumeric253 unique values
0 missing
pginnumeric832 unique values
0 missing
ppginnumeric1072 unique values
0 missing
pfltnumeric2987 unique values
0 missing
vfltnumeric3799 unique values
0 missing
runqsznumeric302 unique values
0 missing
freememnumeric3165 unique values
0 missing
freeswapnumeric7658 unique values
0 missing

107 properties

8192
Number of instances (rows) of the dataset.
22
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.
21
Number of numeric attributes.
1
Number of nominal attributes.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
1328125.96
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
4.07
Second quartile (Median) of skewness among attributes of the numeric type.
0.88
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.
2
The minimal number of distinct values among attributes of the nominal type.
4.55
Percentage of binary attributes.
71.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.1
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.
2
The maximum number of distinct values among attributes of the nominal type.
-0.79
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
21.54
Maximum skewness among attributes of the numeric type.
2.48
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
69.61
Third quartile of kurtosis among attributes of the numeric type.
0.57
Average class difference between consecutive instances.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
422019.43
Maximum standard deviation of attributes of the numeric type.
30.24
Percentage of instances belonging to the least frequent class.
95.45
Percentage of numeric attributes.
986.97
Third quartile of means among attributes of the numeric type.
0.91
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
2477
Number of instances belonging to the least frequent class.
4.55
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.09
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
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
82.69
Mean kurtosis among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
5.64
Third quartile of skewness among attributes of the numeric type.
0.78
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
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
77423.04
Mean of means among attributes of the numeric type.
0.1
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.35
First quartile of kurtosis among attributes of the numeric type.
916.3
Third quartile of standard deviation of attributes of the numeric type.
0.91
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
7.13
First quartile of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.78
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
0.91
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.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
2.03
First quartile of skewness among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.4
Mean skewness among attributes of the numeric type.
14.54
First quartile of standard deviation of attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.78
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
0.09
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
69.76
Percentage of instances belonging to the most frequent class.
38448.59
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.88
Entropy of the target attribute values.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
5715
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
22.82
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
0.9
Minimum kurtosis among attributes of the numeric type.
19.63
Second quartile (Median) of means among attributes of the numeric type.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
618.08
Maximum kurtosis among attributes of the numeric type.
1.13
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

15 tasks

559 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
201 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
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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