Data
ilpd

ilpd

active ARFF Publicly available Visibility: public Uploaded 22-05-2015 by Rafael G. Mantovani
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  • health OpenML-CC18 OpenML100 study_123 study_14 study_34 study_50 study_52 study_7 study_98 study_99 uci
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Author: Bendi Venkata Ramana, M. Surendra Prasad Babu, N. B. Venkateswarlu Source: [UCI](https://archive.ics.uci.edu/ml/datasets/ILPD+(Indian+Liver+Patient+Dataset)) - 2012 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) Indian Liver Patient Dataset This data set contains 416 liver patient records and 167 non liver patient records.The data set was collected from north east of Andhra Pradesh, India. The class label divides the patients into 2 groups (liver patient or not). This data set contains 441 male patient records and 142 female patient records. ### Attribute Information V1. Age of the patient. Any patient whose age exceeded 89 is listed as being of age "90". V2. Gender of the patient V3. Total Bilirubin V4. Direct Bilirubin V5. Alkphos Alkaline Phosphatase V6. Sgpt Alanine Aminotransferase V7. Sgot Aspartate Aminotransferase V8. Total Proteins V9. Albumin V10. A/G Ratio Albumin and Globulin Ratio A feature indicating a train-test split has been removed. ### Relevant Papers 1. Bendi Venkata Ramana, Prof. M. S. Prasad Babu and Prof. N. B. Venkateswarlu, A Critical Comparative Study of Liver Patients from USA and INDIA: An Exploratory Analysis, International Journal of Computer Science Issues, ISSN:1694-0784, May 2012. 2. Bendi Venkata Ramana, Prof. M. S. Prasad Babu and Prof. N. B. Venkateswarlu, A Critical Study of Selected Classification Algorithms for Liver Disease Diagnosis, International Journal of Database Management Systems (IJDMS), Vol.3, No.2, ISSN : 0975-5705, PP 101-114, May 2011.

11 features

Class (target)nominal2 unique values
0 missing
V1numeric72 unique values
0 missing
V2nominal2 unique values
0 missing
V3numeric113 unique values
0 missing
V4numeric80 unique values
0 missing
V5numeric263 unique values
0 missing
V6numeric152 unique values
0 missing
V7numeric177 unique values
0 missing
V8numeric58 unique values
0 missing
V9numeric40 unique values
0 missing
V10numeric70 unique values
0 missing

119 properties

583
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
9
Number of numeric attributes.
2
Number of nominal attributes.
2
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.61
Average class difference between consecutive instances.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
3.28
Mean skewness among attributes of the numeric type.
-0.04
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.71
The predictive accuracy obtained by always predicting the majority class.
82.43
Mean standard deviation of attributes of the numeric type.
0.94
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.02
Number of attributes divided by the number of instances.
149.36
Maximum kurtosis among attributes of the numeric type.
0.8
Minimal entropy among attributes.
0.8
Second quartile (Median) of entropy among attributes.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
181.13
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
290.58
Maximum of means among attributes of the numeric type.
11.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.63
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Maximum mutual information between the nominal attributes and the target attribute.
-0.57
Minimum kurtosis among attributes of the numeric type.
6.48
Second quartile (Median) of means among attributes of the numeric type.
0.29
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
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.37
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
2
The maximum number of distinct values among attributes of the nominal type.
0.95
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
10.51
Maximum skewness among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
3.2
Second quartile (Median) of skewness among attributes of the numeric type.
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
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
288.92
Maximum standard deviation of attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
18.18
Percentage of binary attributes.
6.21
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.44
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
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.8
Average entropy of the attributes.
-0.28
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.8
Third quartile of entropy among attributes.
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.32
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
43.41
Third quartile of kurtosis among attributes of the numeric type.
0.57
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.29
Percentage of instances belonging to the least frequent class.
81.82
Percentage of numeric attributes.
95.31
Third quartile of means among attributes of the numeric type.
0.35
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
29.72
Mean kurtosis among attributes of the numeric type.
167
Number of instances belonging to the least frequent class.
18.18
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.15
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
60.14
Mean of means among attributes of the numeric type.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.8
First quartile of entropy among attributes.
5.71
Third quartile of skewness among attributes of the numeric type.
0.86
Entropy of the target attribute values.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
71.36
Percentage of instances belonging to the most frequent class.
0
Average mutual information between the nominal attributes and the target attribute.
0.44
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.09
First quartile of kurtosis among attributes of the numeric type.
212.78
Third quartile of standard deviation of attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
416
Number of instances belonging to the most frequent class.
166.89
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.31
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.29
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.32
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.8
Maximum entropy among attributes.
2
Average number of distinct values among the attributes of the nominal type.

16 tasks

113466 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
29452 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
45 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - target_feature: Class
1307 runs - target_feature: Class
1306 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
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