Data
yeast_ml8

yeast_ml8

active ARFF Publicly available Visibility: public Uploaded 25-08-2014 by Tobias Kuehn
0 likes downloaded by 8 people , 10 total downloads 0 issues 0 downvotes
  • mythbusting_1 study_1 study_144 study_15 study_20 study_52 study_7
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Source: Unknown - Please cite: Yeast dataset Past Usage: André Elisseeff and Jason Weston. A kernel method for multi-labelled classification. In Thomas G. Dietterich, Susan Becker, and Zoubin Ghahramani, editors, Advances in Neural Information Processing Systems 14, 2002.

117 features

class14 (target)nominal2 unique values
0 missing
attr1numeric2412 unique values
0 missing
attr2numeric2406 unique values
0 missing
attr3numeric2413 unique values
0 missing
attr4numeric2407 unique values
0 missing
attr5numeric2408 unique values
0 missing
attr6numeric2407 unique values
0 missing
attr7numeric2409 unique values
0 missing
attr8numeric2405 unique values
0 missing
attr9numeric2406 unique values
0 missing
attr10numeric2415 unique values
0 missing
attr11numeric2414 unique values
0 missing
attr12numeric2406 unique values
0 missing
attr13numeric2407 unique values
0 missing
attr14numeric2406 unique values
0 missing
attr15numeric2403 unique values
0 missing
attr16numeric2409 unique values
0 missing
attr17numeric2410 unique values
0 missing
attr18numeric2409 unique values
0 missing
attr19numeric2410 unique values
0 missing
attr20numeric2409 unique values
0 missing
attr21numeric2406 unique values
0 missing
attr22numeric2409 unique values
0 missing
attr23numeric2410 unique values
0 missing
attr24numeric2406 unique values
0 missing
attr25numeric2403 unique values
0 missing
attr26numeric2411 unique values
0 missing
attr27numeric2411 unique values
0 missing
attr28numeric2410 unique values
0 missing
attr29numeric2413 unique values
0 missing
attr30numeric2408 unique values
0 missing
attr31numeric2406 unique values
0 missing
attr32numeric2412 unique values
0 missing
attr33numeric2407 unique values
0 missing
attr34numeric2407 unique values
0 missing
attr35numeric2408 unique values
0 missing
attr36numeric2410 unique values
0 missing
attr37numeric2412 unique values
0 missing
attr38numeric2404 unique values
0 missing
attr39numeric2411 unique values
0 missing
attr40numeric2407 unique values
0 missing
attr41numeric2404 unique values
0 missing
attr42numeric2404 unique values
0 missing
attr43numeric2407 unique values
0 missing
attr44numeric2404 unique values
0 missing
attr45numeric2409 unique values
0 missing
attr46numeric2414 unique values
0 missing
attr47numeric2407 unique values
0 missing
attr48numeric2406 unique values
0 missing
attr49numeric2407 unique values
0 missing
attr50numeric2411 unique values
0 missing
attr51numeric2409 unique values
0 missing
attr52numeric2408 unique values
0 missing
attr53numeric2408 unique values
0 missing
attr54numeric2409 unique values
0 missing
attr55numeric2407 unique values
0 missing
attr56numeric2406 unique values
0 missing
attr57numeric2413 unique values
0 missing
attr58numeric2411 unique values
0 missing
attr59numeric2414 unique values
0 missing
attr60numeric2405 unique values
0 missing
attr61numeric2410 unique values
0 missing
attr62numeric2405 unique values
0 missing
attr63numeric2407 unique values
0 missing
attr64numeric2401 unique values
0 missing
attr65numeric2410 unique values
0 missing
attr66numeric2411 unique values
0 missing
attr67numeric2407 unique values
0 missing
attr68numeric2405 unique values
0 missing
attr69numeric2409 unique values
0 missing
attr70numeric2412 unique values
0 missing
attr71numeric2409 unique values
0 missing
attr72numeric2408 unique values
0 missing
attr73numeric2409 unique values
0 missing
attr74numeric2412 unique values
0 missing
attr75numeric2410 unique values
0 missing
attr76numeric2407 unique values
0 missing
attr77numeric2410 unique values
0 missing
attr78numeric2408 unique values
0 missing
attr79numeric2409 unique values
0 missing
attr80numeric2407 unique values
0 missing
attr81numeric2404 unique values
0 missing
attr82numeric2408 unique values
0 missing
attr83numeric2405 unique values
0 missing
attr84numeric2400 unique values
0 missing
attr85numeric2401 unique values
0 missing
attr86numeric2393 unique values
0 missing
attr87numeric2401 unique values
0 missing
attr88numeric2401 unique values
0 missing
attr89numeric2403 unique values
0 missing
attr90numeric2408 unique values
0 missing
attr91numeric2406 unique values
0 missing
attr92numeric2403 unique values
0 missing
attr93numeric2403 unique values
0 missing
attr94numeric2410 unique values
0 missing
attr95numeric2403 unique values
0 missing
attr96numeric2401 unique values
0 missing
attr97numeric2404 unique values
0 missing
attr98numeric2404 unique values
0 missing
attr99numeric2400 unique values
0 missing
attr100numeric2401 unique values
0 missing
attr101numeric2405 unique values
0 missing
attr102numeric2408 unique values
0 missing
attr103numeric2405 unique values
0 missing
class1nominal2 unique values
0 missing
class2nominal2 unique values
0 missing
class3nominal2 unique values
0 missing
class4nominal2 unique values
0 missing
class5nominal2 unique values
0 missing
class6nominal2 unique values
0 missing
class7nominal2 unique values
0 missing
class8nominal2 unique values
0 missing
class9nominal2 unique values
0 missing
class10nominal2 unique values
0 missing
class11nominal2 unique values
0 missing
class12nominal2 unique values
0 missing
class13nominal2 unique values
0 missing

107 properties

2417
Number of instances (rows) of the dataset.
117
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.
103
Number of numeric attributes.
14
Number of nominal attributes.
0.31
First quartile of kurtosis among attributes of the numeric type.
0.1
Third quartile of standard deviation of attributes of the numeric type.
0.5
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
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0
Mean of means among attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.01
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
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0
Average mutual information between the nominal attributes and the target attribute.
0.05
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
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
0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
154.83
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
14
Number of binary attributes.
-0.06
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.5
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.
0.01
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.
0.1
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.01
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
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.35
Mean skewness among attributes of the numeric type.
0.81
Second quartile (Median) of entropy among attributes.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
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
0.02
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
98.59
Percentage of instances belonging to the most frequent class.
0.1
Mean standard deviation of attributes of the numeric type.
0.86
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.11
Entropy of the target attribute values.
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
2383
Number of instances belonging to the most frequent class.
0.38
Minimal entropy among attributes.
0
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.99
Maximum entropy among attributes.
-1.17
Minimum kurtosis among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.01
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
6.69
Maximum kurtosis among attributes of the numeric type.
-0
Minimum of means among attributes of the numeric type.
0.16
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.01
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.05
Number of attributes divided by the number of instances.
0.02
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
11.97
Percentage of binary attributes.
0.92
Third quartile of entropy among attributes.
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
21.83
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.
-0.87
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
2.05
Third quartile of kurtosis among attributes of the numeric type.
0.97
Average class difference between consecutive instances.
0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.85
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0
Third quartile of means among attributes of the numeric type.
0.5
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
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.11
Maximum standard deviation of attributes of the numeric type.
1.41
Percentage of instances belonging to the least frequent class.
88.03
Percentage of numeric attributes.
0.01
Third quartile of mutual information between the nominal attributes and the target attribute.
0.01
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
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.76
Average entropy of the attributes.
34
Number of instances belonging to the least frequent class.
11.97
Percentage of nominal attributes.
0.6
First quartile of entropy among attributes.
0.62
Third quartile of skewness among attributes of the numeric type.
0
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
0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.4
Mean kurtosis among attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

6 tasks

139 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class14
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class14
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class14
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task