Data
cardiotocography

cardiotocography

active ARFF Publicly available Visibility: public Uploaded 21-05-2015 by Rafael G. Mantovani
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  • OpenML100 study_123 study_14 study_34 study_52 study_7 trivial
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Author: J. P. Marques de Sá, J. Bernardes, D. Ayers de Campos. Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Cardiotocography) Please cite: Ayres de Campos et al. (2000) SisPorto 2.0 A Program for Automated Analysis of Cardiotocograms. J Matern Fetal Med 5:311-318, [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) 2126 fetal cardiotocograms (CTGs) were automatically processed and the respective diagnostic features measured. The CTGs were also classified by three expert obstetricians and a consensus classification label assigned to each of them. Classification was both with respect to a morphologic pattern (A, B, C. ...) and to a fetal state (N, S, P). Therefore the dataset can be used either for 10-class or 3-class experiments. ### Attribute Information: LB - FHR baseline (beats per minute) AC - # of accelerations per second FM - # of fetal movements per second UC - # of uterine contractions per second DL - # of light decelerations per second DS - # of severe decelerations per second DP - # of prolongued decelerations per second ASTV - percentage of time with abnormal short term variability MSTV - mean value of short term variability ALTV - percentage of time with abnormal long term variability MLTV - mean value of long term variability Width - width of FHR histogram Min - minimum of FHR histogram Max - Maximum of FHR histogram Nmax - # of histogram peaks Nzeros - # of histogram zeros Mode - histogram mode Mean - histogram mean Median - histogram median Variance - histogram variance Tendency - histogram tendency CLASS - FHR pattern class code (1 to 10) NSP - fetal state class code (N=normal; S=suspect; P=pathologic) ### Relevant Papers: Ayres de Campos et al. (2000) SisPorto 2.0 A Program for Automated Analysis of Cardiotocograms. J Matern Fetal Med 5:311-318

36 features

Class (target)nominal10 unique values
0 missing
V1numeric48 unique values
0 missing
V2numeric979 unique values
0 missing
V3numeric1064 unique values
0 missing
V4numeric48 unique values
0 missing
V5numeric48 unique values
0 missing
V6numeric22 unique values
0 missing
V7numeric96 unique values
0 missing
V8numeric19 unique values
0 missing
V9numeric75 unique values
0 missing
V10numeric57 unique values
0 missing
V11numeric87 unique values
0 missing
V12numeric249 unique values
0 missing
V13numeric15 unique values
0 missing
V14numeric2 unique values
0 missing
V15numeric5 unique values
0 missing
V16numeric154 unique values
0 missing
V17numeric109 unique values
0 missing
V18numeric86 unique values
0 missing
V19numeric18 unique values
0 missing
V20numeric9 unique values
0 missing
V21numeric88 unique values
0 missing
V22numeric103 unique values
0 missing
V23numeric95 unique values
0 missing
V24numeric133 unique values
0 missing
V25numeric3 unique values
0 missing
V26numeric2 unique values
0 missing
V27numeric2 unique values
0 missing
V28numeric2 unique values
0 missing
V29numeric2 unique values
0 missing
V30numeric2 unique values
0 missing
V31numeric2 unique values
0 missing
V32numeric2 unique values
0 missing
V33numeric2 unique values
0 missing
V34numeric2 unique values
0 missing
V35numeric2 unique values
0 missing

19 properties

2126
Number of instances (rows) of the dataset.
36
Number of attributes (columns) of the dataset.
10
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.
35
Number of numeric attributes.
1
Number of nominal attributes.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.61
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
97.22
Percentage of numeric attributes.
27.23
Percentage of instances belonging to the most frequent class.
2.78
Percentage of nominal attributes.
579
Number of instances belonging to the most frequent class.
2.49
Percentage of instances belonging to the least frequent class.
53
Number of instances belonging to the least frequent class.

47 tasks

3594 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
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0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
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