OpenML
caesarian-section

caesarian-section

active ARFF Public Domain (CC0) Visibility: public Uploaded 19-05-2021 by Meilina Reksoprodjo
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We choose age, delivery number, delivery time, blood pressure and heart status. We classify delivery time to Premature, Timely and Latecomer. As like the delivery time we consider blood pressure in three statuses of Low, Normal and High moods. Heart Problem is classified as apt and inept. @attribute 'Age' { 22,26,28,27,32,36,33,23,20,29,25,37,24,18,30,40,31,19,21,35,17,38 } @attribute 'Delivery number' { 1,2,3,4 } @attribute 'Delivery time' { 0,1,2 } -> {0 = timely , 1 = premature , 2 = latecomer} @attribute 'Blood of Pressure' { 2,1,0 } -> {0 = low , 1 = normal , 2 = high } @attribute 'Heart Problem' { 1,0 } -> {0 = apt, 1 = inept } @attribute Caesarian { 0,1 } -> {0 = No, 1 = Yes }

6 features

Agenominal22 unique values
0 missing
Delivery numbernominal4 unique values
0 missing
Delivery timenominal3 unique values
0 missing
Blood of Pressurenominal3 unique values
0 missing
Heart Problemnominal2 unique values
0 missing
Caesariannominal2 unique values
0 missing

19 properties

80
Number of instances (rows) of the dataset.
6
Number of attributes (columns) of the dataset.
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.
0
Number of numeric attributes.
6
Number of nominal attributes.
0.08
Number of attributes divided by the number of instances.
0
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
100
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
2
Number of binary attributes.
33.33
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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