Data
pc1

pc1

active ARFF Publicly available Visibility: public Uploaded 06-10-2014 by Joaquin Vanschoren
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22 features

defects (target)nominal2 unique values
0 missing
locnumeric111 unique values
0 missing
v(g)numeric48 unique values
0 missing
ev(g)numeric27 unique values
0 missing
iv(G)numeric31 unique values
0 missing
Nnumeric312 unique values
0 missing
Vnumeric756 unique values
0 missing
Lnumeric45 unique values
0 missing
Dnumeric613 unique values
0 missing
Inumeric823 unique values
0 missing
Enumeric890 unique values
0 missing
Bnumeric126 unique values
0 missing
Tnumeric886 unique values
0 missing
lOCodenumeric113 unique values
0 missing
lOCommentnumeric53 unique values
0 missing
locCodeAndCommentnumeric24 unique values
0 missing
lOBlanknumeric52 unique values
0 missing
uniq_Opnumeric46 unique values
0 missing
uniq_Opndnumeric106 unique values
0 missing
total_Opnumeric232 unique values
0 missing
total_Opndnumeric203 unique values
0 missing
branchCountnumeric62 unique values
0 missing

107 properties

1109
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.
Second quartile (Median) of entropy among attributes.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.11
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
0.07
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
93.06
Percentage of instances belonging to the most frequent class.
8678.61
Mean standard deviation of attributes of the numeric type.
90.72
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.36
Entropy of the target attribute values.
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
1032
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
15.4
Second quartile (Median) of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
13.73
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.07
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
410.49
Maximum kurtosis among attributes of the numeric type.
0.13
Minimum of means among attributes of the numeric type.
7.43
Second quartile (Median) of skewness among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
28822.88
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
4.55
Percentage of binary attributes.
16.54
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.02
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.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
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.
2.17
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
113.16
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
18.55
Maximum skewness among attributes of the numeric type.
0.15
Minimum standard deviation of attributes of the numeric type.
95.45
Percentage of numeric attributes.
58.7
Third quartile of means among attributes of the numeric type.
0.75
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
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
170643.6
Maximum standard deviation of attributes of the numeric type.
6.94
Percentage 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.
0.07
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
77
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
8.42
Third quartile of skewness among attributes of the numeric type.
0.11
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
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
116.05
Mean kurtosis among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.11
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
56.29
First quartile of kurtosis among attributes of the numeric type.
99.01
Third quartile of standard deviation of attributes of the numeric type.
0.75
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
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1500.99
Mean of means among attributes of the numeric type.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.01
First quartile of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.07
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.11
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
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.57
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.
5.65
First quartile of skewness among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.75
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.
0.07
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.
7.29
First quartile of standard deviation of attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.07
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
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
8.01
Mean skewness among attributes of the numeric type.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: defects
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: defects
0 runs - estimation_procedure: Leave one out - target_feature: defects
0 runs - estimation_procedure: 10% Holdout set - target_feature: defects
0 runs - estimation_procedure: 33% Holdout set - target_feature: defects
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: defects
0 runs - estimation_procedure: Test on Training Data - target_feature: defects
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: defects
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: defects
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: defects
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: defects
Define a new task