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sick

sick

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Author: Source: Unknown - Please cite: ; ; Thyroid disease records supplied by the Garavan Institute and J. Ross ; Quinlan, New South Wales Institute, Syndney, Australia. ; ; 1987. ; sick, negative. | classes age: continuous. sex: M, F. on thyroxine: f, t. query on thyroxine: f, t. on antithyroid medication: f, t. sick: f, t. pregnant: f, t. thyroid surgery: f, t. I131 treatment: f, t. query hypothyroid: f, t. query hyperthyroid: f, t. lithium: f, t. goitre: f, t. tumor: f, t. hypopituitary: f, t. psych: f, t. TSH measured: f, t. TSH: continuous. T3 measured: f, t. T3: continuous. TT4 measured: f, t. TT4: continuous. T4U measured: f, t. T4U: continuous. FTI measured: f, t. FTI: continuous. TBG measured: f, t. TBG: continuous. referral source: WEST, STMW, SVHC, SVI, SVHD, other. Num Instances: 3772 Num Attributes: 30 Num Continuous: 7 (Int 1 / Real 6) Num Discrete: 23 Missing values: 6064 / 5.4% name type enum ints real missing distinct (1) 1 'age' Int 0% 100% 0% 1 / 0% 93 / 2% 0% 2 'sex' Enum 96% 0% 0% 150 / 4% 2 / 0% 0% 3 'on thyroxine' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 4 'query on thyroxine' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 5 'on antithyroid medicati Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 6 'sick' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 7 'pregnant' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 8 'thyroid surgery' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 9 'I131 treatment' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 10 'query hypothyroid' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 11 'query hyperthyroid' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 12 'lithium' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 13 'goitre' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 14 'tumor' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 15 'hypopituitary' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 16 'psych' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 17 'TSH measured' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 18 'TSH' Real 0% 11% 79% 369 / 10% 287 / 8% 2% 19 'T3 measured' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 20 'T3' Real 0% 9% 71% 769 / 20% 69 / 2% 0% 21 'TT4 measured' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 22 'TT4' Real 0% 94% 0% 231 / 6% 241 / 6% 1% 23 'T4U measured' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 24 'T4U' Real 0% 2% 87% 387 / 10% 146 / 4% 1% 25 'FTI measured' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 26 'FTI' Real 0% 90% 0% 385 / 10% 234 / 6% 2% 27 'TBG measured' Enum 100% 0% 0% 0 / 0% 1 / 0% 0% 28 'TBG' Real 0% 0% 0% 3772 /100% 0 / 0% 0% 29 'referral source' Enum 100% 0% 0% 0 / 0% 5 / 0% 0% 30 'Class' Enum 100% 0% 0% 0 / 0% 2 / 0% 0%

30 features

Class (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

107 properties

3772
Number of instances (rows) of the dataset.
30
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
6064
Number of missing values in the dataset.
3772
Number of instances with at least one value missing.
7
Number of numeric attributes.
23
Number of nominal attributes.
0.89
Average class difference between consecutive instances.
0.93
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
0.03
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
0.78
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
0.93
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
0.03
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
0.78
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
0.93
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
0.03
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
0.78
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
0.33
Entropy of the target attribute values.
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.03
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.01
Number of attributes divided by the number of instances.
64.93
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
93.88
Percentage of instances belonging to the most frequent class.
3541
Number of instances belonging to the most frequent class.
1.52
Maximum entropy among attributes.
238.18
Maximum kurtosis among attributes of the numeric type.
110.47
Maximum of means among attributes of the numeric type.
0.06
Maximum mutual information between the nominal attributes and the target attribute.
5
The maximum number of distinct values among attributes of the nominal type.
13.88
Maximum skewness among attributes of the numeric type.
35.6
Maximum standard deviation of attributes of the numeric type.
0.34
Average entropy of the attributes.
51.41
Mean kurtosis among attributes of the numeric type.
46.44
Mean of means among attributes of the numeric type.
0.01
Average mutual information between the nominal attributes and the target attribute.
64.95
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2.09
Average number of distinct values among the attributes of the nominal type.
3.57
Mean skewness among attributes of the numeric type.
19.05
Mean standard deviation of attributes of the numeric type.
-0
Minimal entropy among attributes.
4.07
Minimum kurtosis among attributes of the numeric type.
0.99
Minimum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
1
The minimal number of distinct values among attributes of the nominal type.
1.23
Minimum skewness among attributes of the numeric type.
0.2
Minimum standard deviation of attributes of the numeric type.
6.12
Percentage of instances belonging to the least frequent class.
231
Number of instances belonging to the least frequent class.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.07
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
21
Number of binary attributes.
70
Percentage of binary attributes.
100
Percentage of instances having missing values.
5.36
Percentage of missing values.
23.33
Percentage of numeric attributes.
76.67
Percentage of nominal attributes.
0.1
First quartile of entropy among attributes.
5.98
First quartile of kurtosis among attributes of the numeric type.
1.76
First quartile of means among attributes of the numeric type.
0
First quartile of mutual information between the nominal attributes and the target attribute.
1.26
First quartile of skewness among attributes of the numeric type.
0.67
First quartile of standard deviation of attributes of the numeric type.
0.26
Second quartile (Median) of entropy among attributes.
8.87
Second quartile (Median) of kurtosis among attributes of the numeric type.
28.41
Second quartile (Median) of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
1.54
Second quartile (Median) of skewness among attributes of the numeric type.
22.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.48
Third quartile of entropy among attributes.
90.94
Third quartile of kurtosis among attributes of the numeric type.
108.86
Third quartile of means among attributes of the numeric type.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
4.94
Third quartile of skewness among attributes of the numeric type.
33.72
Third quartile of standard deviation of attributes of the numeric type.
0.96
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.trees.REPTree -L 1
0.87
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.96
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.trees.REPTree -L 2
0.87
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.87
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.04
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.04
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.04
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.67
Standard deviation of the number of distinct values among attributes of the nominal type.
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: Leave one out - target_feature: Class
0 runs - estimation_procedure: 10% Holdout set - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: Test on Training Data - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
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