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hypothyroid

hypothyroid

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Felicia West
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and all others as negative ('N'). Originally converted by Quan Sun.

30 features

binaryClass (target)nominal2 unique values
0 missing
psychnominal2 unique values
0 missing
referral sourcenominal5 unique values
0 missing
TBGnumeric0 unique values
3772 missing
TBG measurednominal1 unique values
0 missing
FTInumeric234 unique values
385 missing
FTI measurednominal2 unique values
0 missing
T4Unumeric146 unique values
387 missing
T4U measurednominal2 unique values
0 missing
TT4numeric241 unique values
231 missing
TT4 measurednominal2 unique values
0 missing
T3numeric69 unique values
769 missing
T3 measurednominal2 unique values
0 missing
TSHnumeric287 unique values
369 missing
TSH measurednominal2 unique values
0 missing
agenumeric93 unique values
1 missing
hypopituitarynominal2 unique values
0 missing
tumornominal2 unique values
0 missing
goitrenominal2 unique values
0 missing
lithiumnominal2 unique values
0 missing
query hyperthyroidnominal2 unique values
0 missing
query hypothyroidnominal2 unique values
0 missing
I131 treatmentnominal2 unique values
0 missing
thyroid surgerynominal2 unique values
0 missing
pregnantnominal2 unique values
0 missing
sicknominal2 unique values
0 missing
on antithyroid medicationnominal2 unique values
0 missing
query on thyroxinenominal2 unique values
0 missing
on thyroxinenominal2 unique values
0 missing
sexnominal2 unique values
150 missing
Show all 30 features

107 properties

NumberOfInstances
3772
Number of instances (rows) of the dataset.
NumberOfFeatures
30
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
6064
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
3772
Number of instances with at least one value missing.
NumberOfNumericFeatures
7
Number of numeric attributes.
NumberOfSymbolicFeatures
23
Number of nominal attributes.
AutoCorrelation
0.86
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.98
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
CfsSubsetEval_DecisionStumpErrRate
0.03
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
CfsSubsetEval_DecisionStumpKappa
0.81
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
CfsSubsetEval_NaiveBayesAUC
0.98
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
CfsSubsetEval_NaiveBayesErrRate
0.03
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
CfsSubsetEval_NaiveBayesKappa
0.81
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
0.98
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
CfsSubsetEval_kNN1NErrRate
0.03
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
CfsSubsetEval_kNN1NKappa
0.81
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
ClassEntropy
0.39
Entropy of the target attribute values.
DecisionStumpAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.87
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
234.83
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
92.29
Percentage of instances belonging to the most frequent class.
MajorityClassSize
3481
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.52
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
238.18
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
110.47
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.01
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
5
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
13.88
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
35.6
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.34
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
51.41
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
46.44
Mean of means among attributes of the numeric type.
MeanMutualInformation
0
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
201.19
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.09
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
3.57
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
19.05
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
-0
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
4.07
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.99
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
1
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
1.23
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.2
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
7.71
Percentage of instances belonging to the least frequent class.
MinorityClassSize
291
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
21
Number of binary attributes.
PercentageOfBinaryFeatures
70
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
100
Percentage of instances having missing values.
PercentageOfMissingValues
5.36
Percentage of missing values.
PercentageOfNumericFeatures
23.33
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
76.67
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.1
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
5.98
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.76
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
1.26
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.67
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.26
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
8.87
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
28.41
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.54
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
22.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
0.48
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
90.94
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
108.86
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
4.94
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
33.72
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.67
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.09
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

15 tasks

Supervised Classification on hypothyroid
522 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on hypothyroid
215 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on hypothyroid
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Data Stream Classification on hypothyroid
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
Clustering on hypothyroid
0 runs
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
Clustering on hypothyroid
0 runs - estimation_procedure: 50 times Clustering
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