Data
colic

colic

active ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
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Author: Mary McLeish & Matt Cecile, University of Guelph Donor: Will Taylor (taylor@pluto.arc.nasa.gov) Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Horse+Colic) - 8/6/89 Please cite: Horse Colic database In this version (version 2), some features were removed. It is unclear why of how this was done.

23 features

surgical_lesion (target)nominal2 unique values
0 missing
surgerynominal2 unique values
2 missing
Agenominal2 unique values
0 missing
rectal_temperaturenumeric40 unique values
69 missing
pulsenumeric54 unique values
26 missing
respiratory_ratenumeric40 unique values
71 missing
temp_extremitiesnominal4 unique values
65 missing
peripheral_pulsenominal4 unique values
83 missing
mucous_membranesnominal6 unique values
48 missing
capillary_refill_timenominal3 unique values
38 missing
painnominal5 unique values
63 missing
peristalsisnominal4 unique values
52 missing
abdominal_distensionnominal4 unique values
65 missing
nasogastric_tubenominal3 unique values
131 missing
nasogastric_refluxnominal3 unique values
133 missing
nasogastric_reflux_PHnumeric24 unique values
299 missing
rectal_examinationnominal4 unique values
128 missing
abdomennominal5 unique values
143 missing
packed_cell_volumenumeric54 unique values
37 missing
total_proteinnumeric84 unique values
43 missing
abdominocentesis_appearancenominal3 unique values
194 missing
abdomcentesis_total_proteinnumeric44 unique values
235 missing
outcomenominal3 unique values
2 missing

107 properties

368
Number of instances (rows) of the dataset.
23
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
1927
Number of missing values in the dataset.
361
Number of instances with at least one value missing.
7
Number of numeric attributes.
16
Number of nominal attributes.
20.14
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
3
Number of binary attributes.
0.03
First quartile of mutual information between the nominal attributes and the target attribute.
0.17
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.62
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
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.56
Average number of distinct values among the attributes of the nominal type.
0.02
First quartile of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.8
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
1.15
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
0.71
Mean skewness among attributes of the numeric type.
1.93
First quartile of standard deviation of attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.18
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
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
12.71
Mean standard deviation of attributes of the numeric type.
1.32
Second quartile (Median) of entropy among attributes.
0.17
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.62
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
0.21
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
63.04
Percentage of instances belonging to the most frequent class.
0.39
Minimal entropy among attributes.
0.84
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.95
Entropy of the target attribute values.
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
232
Number of instances belonging to the most frequent class.
-0.93
Minimum kurtosis among attributes of the numeric type.
30.52
Second quartile (Median) of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.29
Maximum entropy among attributes.
2.95
Minimum of means among attributes of the numeric type.
0.05
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.17
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.18
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
2.65
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0.96
Second quartile (Median) of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
70.76
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
13.04
Percentage of binary attributes.
10.87
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.06
Number of attributes divided by the number of instances.
0.29
Maximum mutual information between the nominal attributes and the target attribute.
-0.46
Minimum skewness among attributes of the numeric type.
98.1
Percentage of instances having missing values.
1.83
Third quartile of entropy among attributes.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
13.89
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
6
The maximum number of distinct values among attributes of the nominal type.
0.71
Minimum standard deviation of attributes of the numeric type.
22.77
Percentage of missing values.
2.03
Third quartile of kurtosis among attributes of the numeric type.
0.54
Average class difference between consecutive instances.
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.58
Maximum skewness among attributes of the numeric type.
36.96
Percentage of instances belonging to the least frequent class.
30.43
Percentage of numeric attributes.
45.66
Third quartile of means among attributes of the numeric type.
0.8
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
0.81
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
28.09
Maximum standard deviation of attributes of the numeric type.
136
Number of instances belonging to the least frequent class.
69.57
Percentage of nominal attributes.
0.09
Third quartile of mutual information between the nominal attributes and the target attribute.
0.18
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
0.25
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
1.45
Average entropy of the attributes.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.07
First quartile of entropy among attributes.
1.39
Third quartile of skewness among attributes of the numeric type.
0.62
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
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.89
Mean kurtosis among attributes of the numeric type.
0.22
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.93
First quartile of kurtosis among attributes of the numeric type.
27.7
Third quartile of standard deviation of attributes of the numeric type.
0.8
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
0.81
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
31.11
Mean of means among attributes of the numeric type.
0.07
Average mutual information between the nominal attributes and the target attribute.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.96
First quartile of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.18
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
0.25
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

10 tasks

754 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
351 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
331 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
189 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
149 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
84 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: surgical_lesion
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: surgical_lesion
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