Data
GCM

GCM

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Multiclass cancer diagnosis using 16063 tumor gene expression signatures. PNAS, VOL 98, no 26, pp. 15149-15154, December 18, 2001. S. Ramaswamy, P. Tamayo, R. Rifkin, S. Mukherjee, C.-H. Yeang, M. Angelo, C. Ladd, M. Reich, E. Latulippe, J.P. Mesirov, T. Poggio, W. Gerald, M. Loda, E.S. Lander and T.R. Golub. Original split: 144 first instances for training, remainder for testing

16064 features

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0 missing
S57153_s_atnumeric103 unique values
0 missing
X53296_s_atnumeric149 unique values
0 missing
X72304_atnumeric105 unique values
0 missing
AFFX-HUMGAPDH/M33197_3_at-2numeric190 unique values
0 missing
AA090439_atnumeric176 unique values
0 missing
AA165144_f_atnumeric122 unique values
0 missing
AA248786_atnumeric138 unique values
0 missing
AA314256_atnumeric138 unique values
0 missing
AA416829_atnumeric104 unique values
0 missing
AA456687_atnumeric157 unique values
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AB002338_atnumeric129 unique values
0 missing
D31184_atnumeric165 unique values
0 missing
H19597_atnumeric141 unique values
0 missing
L20814_at-2numeric147 unique values
0 missing
N44971_atnumeric138 unique values
0 missing
R59531_atnumeric90 unique values
0 missing
T58486_atnumeric92 unique values
0 missing
U76343_atnumeric156 unique values
0 missing
W26496_atnumeric170 unique values
0 missing
W56613_atnumeric157 unique values
0 missing
X98330_at-2numeric111 unique values
0 missing
RC_AA020925_atnumeric104 unique values
0 missing
RC_AA055992_atnumeric166 unique values
0 missing
RC_AA134141_atnumeric160 unique values
0 missing
RC_AA194045_atnumeric170 unique values
0 missing
RC_AA235803_i_atnumeric177 unique values
0 missing
RC_AA256326_atnumeric156 unique values
0 missing
RC_AA282241_atnumeric168 unique values
0 missing
RC_AA382114_atnumeric159 unique values
0 missing
Show first 100 features

107 properties

NumberOfInstances
190
Number of instances (rows) of the dataset.
NumberOfFeatures
16064
Number of attributes (columns) of the dataset.
NumberOfClasses
14
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
16063
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
REPTreeDepth3Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
14439.27
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.92
Second quartile (Median) of skewness among attributes of the numeric type.
RandomTreeDepth1AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
84.55
Number of attributes divided by the number of instances.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
14
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
198.6
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
14
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-13.53
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
RandomTreeDepth1Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
13.68
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
18.63
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
17.02
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.86
Average class difference between consecutive instances.
RandomTreeDepth2AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
8306.13
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
5.26
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
99.99
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
272.3
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.7
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
RandomTreeDepth2ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
10
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
0.01
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.57
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
RandomTreeDepth2Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
15.37
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
3.21
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.38
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
RandomTreeDepth3AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
242.48
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.42
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
3.33
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
405.44
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
0.7
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
RandomTreeDepth3ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
9.12
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.57
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
RandomTreeDepth3Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.38
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
CfsSubsetEval_kNN1NAUC
0.7
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
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
14
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
0.82
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NErrRate
0.57
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
kNN1NAUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
2.06
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
101.08
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.38
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
kNN1NErrRate
0.45
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
15.79
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
382.67
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
3.7
Entropy of the target attribute values.
kNN1NKappa
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
30
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
7.07
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.67
Minimum kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
94.15
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3ErrRate
0.67
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
188.11
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-6243.93
Minimum of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Show all 107 properties

23 tasks

Supervised Classification on GCM
78 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on GCM
38 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on GCM
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GCM
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on GCM
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Clustering on GCM
0 runs - estimation_procedure: 50 times Clustering
Define a new task