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lung-cancer

lung-cancer

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Author: Source: Unknown - Please cite: 1. Title: Lung Cancer Data 2. Source Information: - Data was published in : Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the Plane", Pattern Recognition, Vol. 24, No. 4, pp. 317-324, 1991. - Donor: Stefan Aeberhard, stefan@coral.cs.jcu.edu.au - Date : May, 1992 3. Past Usage: - Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the Plane", Pattern Recognition, Vol. 24, No. 4, pp. 317-324, 1991. - Aeberhard, S., Coomans, D, De Vel, O. "Comparisons of Classification Methods in High Dimensional Settings", submitted to Technometrics. - Aeberhard, S., Coomans, D, De Vel, O. "The Dangers of Bias in High Dimensional Settings", submitted to pattern Recognition. 4. Relevant Information: - This data was used by Hong and Young to illustrate the power of the optimal discriminant plane even in ill-posed settings. Applying the KNN method in the resulting plane gave 77% accuracy. However, these results are strongly biased (See Aeberhard's second ref. above, or email to stefan@coral.cs.jcu.edu.au). Results obtained by Aeberhard et al. are : RDA : 62.5%, KNN 53.1%, Opt. Disc. Plane 59.4% The data described 3 types of pathological lung cancers. The Authors give no information on the individual variables nor on where the data was originally used. - In the original data 4 values for the fifth attribute were -1. These values have been changed to ? (unknown). (*) - In the original data 1 value for the 39 attribute was 4. This value has been changed to ? (unknown). (*) 5. Number of Instances: 32 6. Number of Attributes: 57 (1 class attribute, 56 predictive) 7. Attribute Information: attribute 1 is the class label. - All predictive attributes are nominal, taking on integer values 0-3 8. Missing Attribute Values: Attributes 5 and 39 (*) 9. Class Distribution: - 3 classes, 1.) 9 observations 2.) 13 " 3.) 10 " Information about the dataset CLASSTYPE: nominal CLASSINDEX: first

57 features

class (target)nominal3 unique values
0 missing
attribute2nominal2 unique values
0 missing
attribute3nominal3 unique values
0 missing
attribute4nominal4 unique values
0 missing
attribute5nominal3 unique values
4 missing
attribute6nominal2 unique values
0 missing
attribute7nominal3 unique values
0 missing
attribute8nominal3 unique values
0 missing
attribute9nominal3 unique values
0 missing
attribute10nominal3 unique values
0 missing
attribute11nominal3 unique values
0 missing
attribute12nominal3 unique values
0 missing
attribute13nominal4 unique values
0 missing
attribute14nominal3 unique values
0 missing
attribute15nominal3 unique values
0 missing
attribute16nominal3 unique values
0 missing
attribute17nominal3 unique values
0 missing
attribute18nominal2 unique values
0 missing
attribute19nominal2 unique values
0 missing
attribute20nominal3 unique values
0 missing
attribute21nominal3 unique values
0 missing
attribute22nominal2 unique values
0 missing
attribute23nominal2 unique values
0 missing
attribute24nominal2 unique values
0 missing
attribute25nominal3 unique values
0 missing
attribute26nominal3 unique values
0 missing
attribute27nominal3 unique values
0 missing
attribute28nominal2 unique values
0 missing
attribute29nominal3 unique values
0 missing
attribute30nominal3 unique values
0 missing
attribute31nominal3 unique values
0 missing
attribute32nominal3 unique values
0 missing
attribute33nominal3 unique values
0 missing
attribute34nominal3 unique values
0 missing
attribute35nominal3 unique values
0 missing
attribute36nominal3 unique values
0 missing
attribute37nominal3 unique values
0 missing
attribute38nominal3 unique values
0 missing
attribute39nominal3 unique values
1 missing
attribute40nominal3 unique values
0 missing
attribute41nominal3 unique values
0 missing
attribute42nominal3 unique values
0 missing
attribute43nominal3 unique values
0 missing
attribute44nominal3 unique values
0 missing
attribute45nominal3 unique values
0 missing
attribute46nominal3 unique values
0 missing
attribute47nominal3 unique values
0 missing
attribute48nominal2 unique values
0 missing
attribute49nominal2 unique values
0 missing
attribute50nominal3 unique values
0 missing
attribute51nominal3 unique values
0 missing
attribute52nominal3 unique values
0 missing
attribute53nominal3 unique values
0 missing
attribute54nominal3 unique values
0 missing
attribute55nominal2 unique values
0 missing
attribute56nominal2 unique values
0 missing
attribute57nominal2 unique values
0 missing
Show all 57 features

107 properties

NumberOfInstances
32
Number of instances (rows) of the dataset.
NumberOfFeatures
57
Number of attributes (columns) of the dataset.
NumberOfClasses
3
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
5
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
5
Number of instances with at least one value missing.
NumberOfNumericFeatures
0
Number of numeric attributes.
NumberOfSymbolicFeatures
57
Number of nominal attributes.
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
28.13
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.55
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
RandomTreeDepth2AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.59
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
1.07
Average entropy of the attributes.
MinorityClassSize
9
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile3MutualInformation
0.21
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.63
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
RandomTreeDepth2ErrRate
0.63
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
0.82
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.06
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
RandomTreeDepth2Kappa
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
0.65
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
RandomTreeDepth3AUC
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.59
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
0.15
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.5
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
RandomTreeDepth3ErrRate
0.63
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanNoiseToSignalRatio
5.95
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
13
Number of binary attributes.
Quartile1MutualInformation
0.09
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.59
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.23
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
RandomTreeDepth3Kappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2.81
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
0.63
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
0.48
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
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
0.56
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
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.06
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.59
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.13
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
0.59
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
40.63
Percentage of instances belonging to the most frequent class.
MinAttributeEntropy
0.2
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
1.57
Entropy of the target attribute values.
kNN1NKappa
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
13
Number of instances belonging to the most frequent class.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
1.81
Maximum entropy among attributes.
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
Quartile2MutualInformation
0.12
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
0.59
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.63
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MinMutualInformation
0.01
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
22.81
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
1.78
Number of attributes divided by the number of instances.
MaxMutualInformation
0.47
Maximum mutual information between the nominal attributes and the target attribute.
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
15.63
Percentage of instances having missing values.
Quartile3AttributeEntropy
1.39
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
0.66
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
10.22
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
4
The maximum number of distinct values among attributes of the nominal type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0.27
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.94
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
Show all 107 properties

29 tasks

Supervised Classification on lung-cancer
458 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on lung-cancer
238 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: attribute57
Supervised Classification on lung-cancer
162 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on lung-cancer
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on lung-cancer
183 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: attribute57
Learning Curve on lung-cancer
141 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on lung-cancer
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on lung-cancer
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: attribute57
Supervised Data Stream Classification on lung-cancer
0 runs - estimation_procedure: Interleaved Test then Train - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Data Stream Classification on lung-cancer
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering - target_feature: Pneumonia
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
Clustering on lung-cancer
0 runs - estimation_procedure: 50 times Clustering
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