Data
yeast_gene

yeast_gene

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Systematic determination of genetic network architecture. Nature Genetics, 1999 Jul;22(3):281-5. Data also used in Biclustering of Expression Data, by Yizong Cheng and George M. Church (web supplement) S. Tavazoie, J.D. Hughes, M.J. Campbell, R.J. Cho, G.M. Church. Dataset (17 instances x 1884 genes) in ARFF format, no labelled classes

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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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YNL306Wnumeric10 unique values
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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
YAR044Wnumeric5 unique values
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0 missing
YDR470Cnumeric6 unique values
0 missing
YGL126Wnumeric8 unique values
0 missing
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0 missing
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0 missing
YMR130Wnumeric9 unique values
0 missing
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0 missing
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0 missing
YBR285Wnumeric8 unique values
0 missing
YDR019Cnumeric13 unique values
0 missing
YDR471Wnumeric13 unique values
0 missing
YGL127Cnumeric6 unique values
0 missing
YIL144Wnumeric7 unique values
0 missing
YKL087Cnumeric10 unique values
0 missing
YLR229Cnumeric12 unique values
0 missing
YMR131Cnumeric13 unique values
0 missing
YNL312Wnumeric14 unique values
0 missing
YOR330Cnumeric8 unique values
0 missing
YAR053Wnumeric7 unique values
0 missing
YBR289Wnumeric8 unique values
0 missing
YDR020Cnumeric10 unique values
0 missing
YDR473Cnumeric6 unique values
0 missing
YGL128Cnumeric5 unique values
0 missing
YIL145Cnumeric10 unique values
0 missing
YKL089Wnumeric8 unique values
0 missing
YLR231Cnumeric10 unique values
0 missing
YMR132Cnumeric10 unique values
0 missing
YNL313Cnumeric9 unique values
0 missing
YOR333Cnumeric4 unique values
0 missing
YAR060Cnumeric4 unique values
0 missing
YBR290Wnumeric9 unique values
0 missing
YDR022Cnumeric6 unique values
0 missing
YDR476Cnumeric8 unique values
0 missing
YGL129Cnumeric7 unique values
0 missing
YIL146Cnumeric3 unique values
0 missing
YKL091Cnumeric10 unique values
0 missing
YLR232Wnumeric3 unique values
0 missing
YMR133Wnumeric3 unique values
0 missing
YNL314Wnumeric6 unique values
0 missing
YOR338Wnumeric7 unique values
0 missing
YAR061Wnumeric3 unique values
0 missing
YBR292Cnumeric7 unique values
0 missing
YDR025Wnumeric15 unique values
0 missing
YDR477Wnumeric9 unique values
0 missing
YGL130Wnumeric6 unique values
0 missing
YIL150Cnumeric2 unique values
0 missing
YKL092Cnumeric7 unique values
0 missing
YLR233Cnumeric8 unique values
0 missing
YMR134Wnumeric13 unique values
0 missing
YNL325Cnumeric4 unique values
0 missing
YOR339Cnumeric5 unique values
0 missing
YAR064Wnumeric7 unique values
0 missing
YBR293Wnumeric7 unique values
0 missing
YDR029Wnumeric5 unique values
0 missing
YDR478Wnumeric8 unique values
0 missing
YGL131Cnumeric3 unique values
0 missing
YIL153Wnumeric7 unique values
0 missing
YKL095Wnumeric5 unique values
0 missing
YLR234Wnumeric4 unique values
0 missing
YMR136Wnumeric10 unique values
0 missing
YNL327Wnumeric16 unique values
0 missing
YOR341Wnumeric12 unique values
0 missing
YAR066Wnumeric5 unique values
0 missing
YBR295Wnumeric3 unique values
0 missing
YDR033Wnumeric15 unique values
0 missing
YDR479Cnumeric7 unique values
0 missing
YGL141Wnumeric3 unique values
0 missing
YIL155Cnumeric5 unique values
0 missing
YKL096Wnumeric15 unique values
0 missing
YLR236Cnumeric5 unique values
0 missing
YMR139Wnumeric6 unique values
0 missing
YNL328Cnumeric3 unique values
0 missing
YOR342Cnumeric14 unique values
0 missing
YAR069Cnumeric4 unique values
0 missing
YBR296Cnumeric4 unique values
0 missing
YDR035Wnumeric14 unique values
0 missing
YDR485Cnumeric6 unique values
0 missing
YGL144Cnumeric3 unique values
0 missing
YIL156Wnumeric4 unique values
0 missing
YKL096W-Anumeric16 unique values
0 missing
YLR243Wnumeric10 unique values
0 missing
YMR141Cnumeric9 unique values
0 missing
YNL329Cnumeric11 unique values
0 missing
YOR345Cnumeric3 unique values
0 missing
YAR070Cnumeric4 unique values
0 missing
YBR297Wnumeric5 unique values
0 missing
YDR038Cnumeric13 unique values
0 missing
YDR487Cnumeric13 unique values
0 missing
YGL151Wnumeric5 unique values
0 missing
YIL157Cnumeric7 unique values
0 missing
YKL100Cnumeric10 unique values
0 missing
YLR248Wnumeric7 unique values
0 missing
YMR143Wnumeric15 unique values
0 missing
YNL333Wnumeric9 unique values
0 missing
YOR347Cnumeric5 unique values
0 missing
YAR071Wnumeric17 unique values
0 missing
YBR298Cnumeric4 unique values
0 missing
YDR039Cnumeric12 unique values
0 missing
YDR488Cnumeric6 unique values
0 missing
YGL155Wnumeric3 unique values
0 missing
YIL158Wnumeric13 unique values
0 missing
YKL101Wnumeric16 unique values
0 missing
YLR249Wnumeric15 unique values
0 missing
YMR144Wnumeric9 unique values
0 missing
YNL335Wnumeric2 unique values
0 missing
YOR352Wnumeric5 unique values
0 missing
YAR073Wnumeric6 unique values
0 missing
YBR299Wnumeric5 unique values
0 missing
YDR042Cnumeric10 unique values
0 missing
YDR489Wnumeric8 unique values
0 missing
YGL156Wnumeric6 unique values
0 missing
YIL159Wnumeric6 unique values
0 missing
YKL102Cnumeric2 unique values
0 missing
YLR250Wnumeric10 unique values
0 missing
YMR145Cnumeric15 unique values
0 missing
YNL336Wnumeric9 unique values
0 missing
YOR356Wnumeric10 unique values
0 missing
YAR075Wnumeric9 unique values
0 missing
YBR302Cnumeric9 unique values
0 missing
YDR044Wnumeric15 unique values
0 missing
YDR490Cnumeric6 unique values
0 missing
YGL160Wnumeric4 unique values
0 missing
YIL162Wnumeric6 unique values
0 missing
YKL103Cnumeric11 unique values
0 missing
YLR251Wnumeric7 unique values
0 missing
YMR146Cnumeric14 unique values
0 missing
YNL339Cnumeric16 unique values
0 missing
YOR357Cnumeric8 unique values
0 missing
YBL001Cnumeric12 unique values
0 missing
YCL002Cnumeric6 unique values
0 missing
YDR045Cnumeric12 unique values
0 missing
YDR491Cnumeric6 unique values
0 missing
YGL166Wnumeric5 unique values
0 missing
YIL163Cnumeric2 unique values
0 missing
YKL105Cnumeric9 unique values
0 missing
YLR252Wnumeric9 unique values
0 missing
YMR147Wnumeric4 unique values
0 missing
YNR001Cnumeric15 unique values
0 missing
YOR358Wnumeric5 unique values
0 missing
YBL002Wnumeric16 unique values
0 missing
YCL003Wnumeric3 unique values
0 missing
YDR046Cnumeric15 unique values
0 missing
YDR492Wnumeric14 unique values
0 missing
YGL170Cnumeric4 unique values
0 missing
YIL167Wnumeric6 unique values
0 missing
YKL107Wnumeric2 unique values
0 missing
YLR253Wnumeric6 unique values
0 missing
YMR152Wnumeric7 unique values
0 missing
YNR002Cnumeric4 unique values
0 missing
YOR362Cnumeric12 unique values
0 missing
YBL003Cnumeric16 unique values
0 missing
YCL007Cnumeric13 unique values
0 missing
YDR048Cnumeric3 unique values
0 missing
YDR493Wnumeric12 unique values
0 missing
YGL179Cnumeric4 unique values
0 missing
YIL169Cnumeric10 unique values
0 missing
YKL108Wnumeric10 unique values
0 missing
YLR254Cnumeric13 unique values
0 missing

107 properties

17
Number of instances (rows) of the dataset.
2884
Number of attributes (columns) of the dataset.
0
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.
2884
Number of numeric attributes.
0
Number of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0
Percentage of nominal attributes.
0.36
Third quartile of skewness among attributes of the numeric type.
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.39
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
39.94
Third quartile of standard deviation of attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
212.73
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.76
First quartile of kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
128.53
First quartile of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
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.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
-0.61
First quartile of skewness among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.1
Mean skewness among attributes of the numeric type.
23.6
First quartile of standard deviation of attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
33.14
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
-0.05
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
205.15
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-2.27
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
17
Maximum kurtosis among attributes of the numeric type.
-1
Minimum of means among attributes of the numeric type.
-0.13
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
539.12
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
31.18
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
169.65
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
Third quartile of entropy among attributes.
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.
The maximum number of distinct values among attributes of the nominal type.
-4.12
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
1.05
Third quartile of kurtosis among attributes of the numeric type.
-19.88
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.12
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
288.88
Third quartile of means among attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
115.45
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.

13 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: YPR204W
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: YPR204W
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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