Data
BNG(colic.ORIG)

BNG(colic.ORIG)

active ARFF Publicly available Visibility: public Uploaded 28-04-2014 by Jan van Rijn
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28 features

surgical_lesion (target)nominal2 unique values
0 missing
surgerynominal2 unique values
0 missing
Agenominal2 unique values
0 missing
Hospital_Numbernominal338 unique values
0 missing
rectal_temperaturenumeric753198 unique values
0 missing
pulsenumeric992613 unique values
0 missing
respiratory_ratenumeric989417 unique values
0 missing
temperature_of_extremitiesnominal4 unique values
0 missing
peripheral_pulsenominal4 unique values
0 missing
mucous_membranesnominal6 unique values
0 missing
capillary_refill_timenominal3 unique values
0 missing
painnominal5 unique values
0 missing
peristalsisnominal4 unique values
0 missing
abdominal_distensionnominal4 unique values
0 missing
nasogastric_tubenominal3 unique values
0 missing
nasogastric_refluxnominal3 unique values
0 missing
nasogastric_reflux_PHnumeric813172 unique values
0 missing
rectal_examination_-_fecesnominal4 unique values
0 missing
abdomennominal5 unique values
0 missing
packed_cell_volumenumeric981363 unique values
0 missing
total_proteinnumeric941681 unique values
0 missing
abdominocentesis_appearancenominal3 unique values
0 missing
abdomcentesis_total_proteinnumeric713656 unique values
0 missing
outcomenominal3 unique values
0 missing
site_of_lesionnominal63 unique values
0 missing
type_of_lesionnominal8 unique values
0 missing
subtype_of_lesionnominal2 unique values
0 missing
pathology_cp_datanominal2 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
28
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.
7
Number of numeric attributes.
21
Number of nominal attributes.
0.25
First quartile of skewness among attributes of the numeric type.
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.88
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
73.48
Standard deviation of the number of distinct values among attributes of the nominal type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
22.38
Average number of distinct values among the attributes of the nominal type.
1.31
First quartile of standard deviation of attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.17
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
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.6
Mean skewness among attributes of the numeric type.
1.32
Second quartile (Median) of entropy among attributes.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.64
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
0.22
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
63.76
Percentage of instances belonging to the most frequent class.
12.65
Mean standard deviation of attributes of the numeric type.
0.49
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.94
Entropy of the target attribute values.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
637594
Number of instances belonging to the most frequent class.
0.05
Minimal entropy among attributes.
34.15
Second quartile (Median) of means among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
8.38
Maximum entropy among attributes.
-0.7
Minimum kurtosis among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
9.09
Maximum kurtosis among attributes of the numeric type.
2.32
Minimum of means among attributes of the numeric type.
0.87
Second quartile (Median) of skewness among attributes of the numeric type.
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
69.89
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
10.33
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
0.24
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
17.86
Percentage of binary attributes.
0
Percentage of instances having missing values.
1.82
Third quartile of entropy among attributes.
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
31.27
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
338
The maximum number of distinct values among attributes of the nominal type.
-2.34
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
5.27
Third quartile of kurtosis among attributes of the numeric type.
0.54
Average class difference between consecutive instances.
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.84
Maximum skewness among attributes of the numeric type.
0.65
Minimum standard deviation of attributes of the numeric type.
25
Percentage of numeric attributes.
44.82
Third quartile of means among attributes of the numeric type.
0.88
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
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
27.88
Maximum standard deviation of attributes of the numeric type.
36.24
Percentage of instances belonging to the least frequent class.
75
Percentage of nominal attributes.
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
0.17
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
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.83
Average entropy of the attributes.
362406
Number of instances belonging to the least frequent class.
0.95
First quartile of entropy among attributes.
1.03
Third quartile of skewness among attributes of the numeric type.
0.64
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
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2.28
Mean kurtosis among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.23
First quartile of kurtosis among attributes of the numeric type.
27.19
Third quartile of standard deviation of attributes of the numeric type.
0.88
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
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
31.59
Mean of means among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
6.74
First quartile of means among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.17
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
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.03
Average mutual information between the nominal attributes and the target attribute.
0.63
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.64
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
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
59.65
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
5
Number of binary attributes.

11 tasks

20 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
20 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: pathology_cp_data
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: pathology_cp_data
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: pathology_cp_data
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: pathology_cp_data
123 runs - estimation_procedure: Interleaved Test then Train - target_feature: pathology_cp_data
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: surgical_lesion
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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