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dis

dis

active ARFF public Visibility: public Uploaded 06-04-2017 by Arnold
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dis-pmlb

30 features

class (target)nominal2 unique values
0 missing
psychnominal2 unique values
0 missing
referral_sourcenominal5 unique values
0 missing
TBGnominal1 unique values
0 missing
TBG_measurednominal1 unique values
0 missing
FTInumeric235 unique values
0 missing
FTI_measurednominal2 unique values
0 missing
T4Unumeric147 unique values
0 missing
T4U_measurednominal2 unique values
0 missing
TT4numeric242 unique values
0 missing
TT4_measurednominal2 unique values
0 missing
T3numeric70 unique values
0 missing
T3_measurednominal2 unique values
0 missing
TSHnumeric288 unique values
0 missing
TSH_measurednominal2 unique values
0 missing
agenumeric94 unique values
0 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
sexnominal3 unique values
0 missing
Show all 30 features

62 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
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
6
Number of numeric attributes.
NumberOfSymbolicFeatures
24
Number of nominal attributes.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
66.67
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
20
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
80
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.09
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.83
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
42.54
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0.72
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
0.01
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
20.79
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.24
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.8
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
88.44
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
0.32
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
57.95
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
0.48
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
-0
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
122.39
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
1.13
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
97.8
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.97
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
83.62
Mean of means among attributes of the numeric type.
ClassEntropy
0.11
Entropy of the target attribute values.
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
218.73
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
98.46
Percentage of instances belonging to the most frequent class.
MajorityClassSize
3714
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.52
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
1.22
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
126.28
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0
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
1.41
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
98.64
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.33
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.74
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
20
Number of binary attributes.
MeanMutualInformation
0
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
633.36
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.08
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.5
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
58.92
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
-0
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.85
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
31.1
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
-0.17
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
20.65
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
1.54
Percentage of instances belonging to the least frequent class.
MinorityClassSize
58
Number of instances belonging to the least frequent class.
Show all 62 properties

22 tasks

Supervised Classification on dis
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on dis
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on dis
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on dis
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
Clustering on dis
0 runs - estimation_procedure: 50 times Clustering
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