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qsar-biodeg

qsar-biodeg

active ARFF Publicly available Visibility: public Uploaded 25-05-2015 by Rafael Gomes Mantovani
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42 features

Class (target)nominal2 unique values
0 missing
V1numeric440 unique values
0 missing
V2numeric1022 unique values
0 missing
V3numeric11 unique values
0 missing
V4numeric4 unique values
0 missing
V5numeric16 unique values
0 missing
V6numeric13 unique values
0 missing
V7numeric15 unique values
0 missing
V8numeric188 unique values
0 missing
V9numeric15 unique values
0 missing
V10numeric12 unique values
0 missing
V11numeric21 unique values
0 missing
V12numeric384 unique values
0 missing
V13numeric756 unique values
0 missing
V14numeric373 unique values
0 missing
V15numeric510 unique values
0 missing
V16numeric24 unique values
0 missing
V17numeric167 unique values
0 missing
V18numeric125 unique values
0 missing
V19numeric3 unique values
0 missing
V20numeric4 unique values
0 missing
V21numeric4 unique values
0 missing
V22numeric352 unique values
0 missing
V23numeric13 unique values
0 missing
V24numeric2 unique values
0 missing
V25numeric2 unique values
0 missing
V26numeric4 unique values
0 missing
V27numeric329 unique values
0 missing
V28numeric205 unique values
0 missing
V29numeric2 unique values
0 missing
V30numeric470 unique values
0 missing
V31numeric553 unique values
0 missing
V32numeric8 unique values
0 missing
V33numeric11 unique values
0 missing
V34numeric16 unique values
0 missing
V35numeric8 unique values
0 missing
V36numeric705 unique values
0 missing
V37numeric624 unique values
0 missing
V38numeric8 unique values
0 missing
V39numeric862 unique values
0 missing
V40numeric5 unique values
0 missing
V41numeric17 unique values
0 missing

107 properties

1055
Number of instances (rows) of the dataset.
42
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.
41
Number of numeric attributes.
1
Number of nominal attributes.
0.24
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.38
First quartile of kurtosis among attributes of the numeric type.
2.03
Third quartile of standard deviation of attributes of the numeric type.
0.82
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
0.17
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2.68
Mean of means among attributes of the numeric type.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.1
First quartile of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.18
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
0.21
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.61
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.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.58
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
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.83
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.
1.41
First quartile of skewness among attributes of the numeric type.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.82
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.
0.17
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.
3.8
Mean skewness among attributes of the numeric type.
0.24
First quartile of standard deviation of attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.18
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
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.59
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.58
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
0.18
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
66.26
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
11.77
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.92
Entropy of the target attribute values.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
699
Number of instances belonging to the most frequent class.
-0.22
Minimum kurtosis among attributes of the numeric type.
1.13
Second quartile (Median) of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.2
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.29
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
812.72
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2.62
Second quartile (Median) of skewness among attributes of the numeric type.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
37.06
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
2.38
Percentage of binary attributes.
0.83
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
0.04
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-1.76
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.21
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.
0.03
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
46.89
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
26.85
Maximum skewness among attributes of the numeric type.
33.74
Percentage of instances belonging to the least frequent class.
97.62
Percentage of numeric attributes.
2.61
Third quartile of means among attributes of the numeric type.
0.82
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
0.17
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.9
Maximum standard deviation of attributes of the numeric type.
356
Number of instances belonging to the least frequent class.
2.38
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.18
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
0.21
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
5.71
Third quartile of skewness among attributes of the numeric type.
0.58
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
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
44.71
Mean kurtosis among attributes of the numeric type.

11 tasks

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