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rsctc2010_3

rsctc2010_3

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Data from the RSCTC 2010 Discovery Challenge. Example datasets for 6 different problems of DNA microarray data analysis and classification. All datasets contain gene expression data characterized by values of 20,000 - 65,000 attributes. Samples are assigned to several (2-10) classes. All attributes are numeric and represent measurements from DNA microarrays. Source: http://tunedit.org/challenge/RSCTC-2010-A

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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
Var16905numeric95 unique values
0 missing
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0 missing
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0 missing
Var17673numeric85 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
Var19465numeric93 unique values
0 missing
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0 missing
Var19977numeric94 unique values
0 missing
Var20233numeric92 unique values
0 missing
Var20489numeric92 unique values
0 missing
Var20745numeric93 unique values
0 missing
Var21001numeric93 unique values
0 missing
Var21257numeric91 unique values
0 missing
Var21513numeric93 unique values
0 missing
Var21769numeric91 unique values
0 missing
Var22025numeric94 unique values
0 missing
Var10numeric91 unique values
0 missing
Var266numeric94 unique values
0 missing
Var522numeric93 unique values
0 missing
Var778numeric90 unique values
0 missing
Var1034numeric91 unique values
0 missing
Var1290numeric92 unique values
0 missing
Var1546numeric94 unique values
0 missing
Var1802numeric93 unique values
0 missing
Var2058numeric93 unique values
0 missing
Var2314numeric92 unique values
0 missing
Var2570numeric90 unique values
0 missing
Var2826numeric89 unique values
0 missing
Var3082numeric94 unique values
0 missing
Var3338numeric95 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
Var4618numeric90 unique values
0 missing
Var4874numeric89 unique values
0 missing
Var5130numeric91 unique values
0 missing
Var5386numeric90 unique values
0 missing
Var5642numeric93 unique values
0 missing
Var5898numeric86 unique values
0 missing
Var6154numeric93 unique values
0 missing
Var6410numeric94 unique values
0 missing
Var6666numeric94 unique values
0 missing
Var6922numeric90 unique values
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Var7178numeric90 unique values
0 missing
Var7434numeric89 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
Var11274numeric91 unique values
0 missing
Var11530numeric88 unique values
0 missing
Var11786numeric93 unique values
0 missing
Var12042numeric91 unique values
0 missing
Var12298numeric93 unique values
0 missing
Var12554numeric91 unique values
0 missing
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0 missing
Var13066numeric95 unique values
0 missing
Var13322numeric94 unique values
0 missing
Var13578numeric95 unique values
0 missing
Var13834numeric94 unique values
0 missing
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0 missing
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0 missing
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0 missing
Var15626numeric94 unique values
0 missing
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0 missing
Var16138numeric92 unique values
0 missing
Var16394numeric92 unique values
0 missing
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0 missing
Var16906numeric88 unique values
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0 missing
Var17418numeric94 unique values
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0 missing
Var17930numeric95 unique values
0 missing
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0 missing
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0 missing
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0 missing
Var19210numeric92 unique values
0 missing
Var19466numeric92 unique values
0 missing
Var19722numeric94 unique values
0 missing
Var19978numeric92 unique values
0 missing
Var20234numeric93 unique values
0 missing
Var20490numeric92 unique values
0 missing
Var20746numeric93 unique values
0 missing
Var21002numeric93 unique values
0 missing
Var21258numeric83 unique values
0 missing
Var21514numeric95 unique values
0 missing
Var21770numeric92 unique values
0 missing
Var22026numeric90 unique values
0 missing
Var11numeric90 unique values
0 missing
Var267numeric94 unique values
0 missing
Var523numeric91 unique values
0 missing
Var779numeric91 unique values
0 missing
Var1035numeric93 unique values
0 missing
Var1291numeric90 unique values
0 missing
Var1547numeric90 unique values
0 missing
Var1803numeric89 unique values
0 missing
Var2059numeric89 unique values
0 missing
Var2315numeric90 unique values
0 missing
Var2571numeric92 unique values
0 missing
Var2827numeric92 unique values
0 missing
Var3083numeric90 unique values
0 missing
Var3339numeric93 unique values
0 missing
Var3595numeric94 unique values
0 missing
Var3851numeric92 unique values
0 missing
Var4107numeric93 unique values
0 missing
Var4363numeric90 unique values
0 missing
Var4619numeric93 unique values
0 missing
Var4875numeric93 unique values
0 missing
Var5131numeric91 unique values
0 missing
Var5387numeric92 unique values
0 missing
Var5643numeric88 unique values
0 missing
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0 missing
Var6155numeric94 unique values
0 missing
Var6411numeric93 unique values
0 missing
Var6667numeric93 unique values
0 missing
Var6923numeric95 unique values
0 missing
Var7179numeric93 unique values
0 missing
Var7435numeric93 unique values
0 missing
Var7691numeric89 unique values
0 missing
Var7947numeric89 unique values
0 missing
Var8203numeric93 unique values
0 missing
Var8459numeric91 unique values
0 missing
Var8715numeric93 unique values
0 missing
Var8971numeric88 unique values
0 missing
Var9227numeric93 unique values
0 missing
Var9483numeric93 unique values
0 missing
Var9739numeric90 unique values
0 missing
Var9995numeric93 unique values
0 missing
Var10251numeric90 unique values
0 missing
Var10507numeric93 unique values
0 missing
Var10763numeric93 unique values
0 missing
Var11019numeric92 unique values
0 missing
Var11275numeric88 unique values
0 missing
Var11531numeric93 unique values
0 missing
Var11787numeric92 unique values
0 missing
Var12043numeric91 unique values
0 missing
Var12299numeric90 unique values
0 missing
Var12555numeric89 unique values
0 missing
Var12811numeric90 unique values
0 missing
Var13067numeric92 unique values
0 missing
Var13323numeric94 unique values
0 missing
Var13579numeric90 unique values
0 missing
Var13835numeric91 unique values
0 missing
Var14091numeric93 unique values
0 missing
Var14347numeric92 unique values
0 missing
Var14603numeric92 unique values
0 missing
Var14859numeric94 unique values
0 missing
Var15115numeric89 unique values
0 missing
Var15371numeric91 unique values
0 missing
Var15627numeric93 unique values
0 missing
Var15883numeric92 unique values
0 missing
Var16139numeric92 unique values
0 missing
Var16395numeric91 unique values
0 missing
Var16651numeric93 unique values
0 missing
Var16907numeric92 unique values
0 missing
Var17163numeric89 unique values
0 missing
Var17419numeric91 unique values
0 missing
Var17675numeric90 unique values
0 missing
Var17931numeric93 unique values
0 missing
Var18187numeric92 unique values
0 missing
Var18443numeric93 unique values
0 missing
Var18699numeric92 unique values
0 missing
Var18955numeric92 unique values
0 missing
Var19211numeric90 unique values
0 missing
Var19467numeric94 unique values
0 missing
Var19723numeric93 unique values
0 missing
Var19979numeric93 unique values
0 missing
Var20235numeric91 unique values
0 missing
Var20491numeric94 unique values
0 missing
Var20747numeric92 unique values
0 missing
Var21003numeric91 unique values
0 missing
Var21259numeric94 unique values
0 missing
Var21515numeric92 unique values
0 missing
Var21771numeric93 unique values
0 missing
Var22027numeric92 unique values
0 missing
Var12numeric91 unique values
0 missing
Var268numeric93 unique values
0 missing
Var524numeric91 unique values
0 missing
Var780numeric88 unique values
0 missing
Var1036numeric91 unique values
0 missing
Var1292numeric92 unique values
0 missing
Var1548numeric91 unique values
0 missing
Var1804numeric89 unique values
0 missing
Var2060numeric94 unique values
0 missing
Var2316numeric93 unique values
0 missing
Var2572numeric92 unique values
0 missing
Var2828numeric90 unique values
0 missing
Var3084numeric93 unique values
0 missing
Var3340numeric91 unique values
0 missing
Var3596numeric92 unique values
0 missing
Var3852numeric90 unique values
0 missing
Var4108numeric92 unique values
0 missing
Var4364numeric91 unique values
0 missing
Var4620numeric93 unique values
0 missing
Var4876numeric86 unique values
0 missing
Var5132numeric92 unique values
0 missing
Var5388numeric93 unique values
0 missing
Var5644numeric91 unique values
0 missing
Var5900numeric90 unique values
0 missing
Var6156numeric93 unique values
0 missing
Var6412numeric91 unique values
0 missing
Var6668numeric94 unique values
0 missing
Var6924numeric90 unique values
0 missing
Var7180numeric92 unique values
0 missing
Var7436numeric92 unique values
0 missing
Var7692numeric89 unique values
0 missing
Var7948numeric90 unique values
0 missing
Var8204numeric93 unique values
0 missing
Var8460numeric91 unique values
0 missing
Var8716numeric92 unique values
0 missing
Var8972numeric93 unique values
0 missing
Var9228numeric91 unique values
0 missing

107 properties

95
Number of instances (rows) of the dataset.
22278
Number of attributes (columns) of the dataset.
5
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.
22277
Number of numeric attributes.
1
Number of nominal attributes.
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
5.48
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.33
Second quartile (Median) of skewness among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
234.51
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
5
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.45
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.49
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.
5
The maximum number of distinct values among attributes of the nominal type.
-4.68
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.56
Maximum skewness among attributes of the numeric type.
0.1
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.17
Third quartile of kurtosis among attributes of the numeric type.
0.21
Average class difference between consecutive instances.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.6
Maximum standard deviation of attributes of the numeric type.
5.26
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.
1.54
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
0.49
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
5
Number of instances belonging to the least frequent class.
0
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.36
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
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.58
Mean kurtosis among attributes of the numeric type.
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.16
Third quartile of skewness among attributes of the numeric type.
0.54
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.08
Mean of means among attributes of the numeric type.
0.28
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.71
First quartile of kurtosis among attributes of the numeric type.
0.52
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
0.49
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.44
First quartile of means among attributes of the numeric type.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.36
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
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.49
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.54
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
0.75
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.
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
5
Average number of distinct values among the attributes of the nominal type.
-0.81
First quartile of skewness among attributes of the numeric type.
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.36
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
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.27
Mean skewness among attributes of the numeric type.
0.35
First quartile of standard deviation of attributes of the numeric type.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.54
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
0.31
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
28.42
Percentage of instances belonging to the most frequent class.
0.44
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.49
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.18
Entropy of the target attribute values.
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
27
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.04
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.56
Minimum kurtosis among attributes of the numeric type.
0.92
Second quartile (Median) of means among attributes of the numeric type.
0.49
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.6
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
29.99
Maximum kurtosis among attributes of the numeric type.
-0.55
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

14 tasks

9 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Decision
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
Define a new task