Contraceptive Method Choice

Donated on 7/6/1997

Dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey.

Dataset Characteristics

Multivariate

Subject Area

Health and Medicine

Associated Tasks

Classification

Feature Type

Categorical, Integer

# Instances

1473

# Features

9

Dataset Information

Additional Information

This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of interview. The problem is to predict the current contraceptive method choice (no use, long-term methods, or short-term methods) of a woman based on her demographic and socio-economic characteristics.

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
wife_ageFeatureIntegerAgeno
wife_eduFeatureCategoricalEducation Levelno
husband_eduFeatureCategoricalEducation Levelno
num_childrenFeatureIntegerOtherno
wife_religionFeatureBinaryOtherno
wife_workingFeatureBinaryOccupationno
husband_occupationFeatureCategoricalOccupationno
standard_of_living_indexFeatureCategoricalno
media_exposureFeatureBinaryno
contraceptive_methodTargetCategoricalno

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Additional Variable Information

1. Wife's age (numerical) 2. Wife's education (categorical) 1=low, 2, 3, 4=high 3. Husband's education (categorical) 1=low, 2, 3, 4=high 4. Number of children ever born (numerical) 5. Wife's religion (binary) 0=Non-Islam, 1=Islam 6. Wife's now working? (binary) 0=Yes, 1=No 7. Husband's occupation (categorical) 1, 2, 3, 4 8. Standard-of-living index (categorical) 1=low, 2, 3, 4=high 9. Media exposure (binary) 0=Good, 1=Not good 10. Contraceptive method used (class attribute) 1=No-use, 2=Long-term, 3=Short-term

Papers Citing this Dataset

SECRET: Semantically Enhanced Classification of Real-world Tasks

By Ayten Akmandor, Jorge Ortiz, Irene Manotas, Bongjun Ko, Niraj Jha. 2019

Published in ArXiv.

Transfer learning for class imbalance problems with inadequate data

By Samir Al-Stouhi, Chandan Reddy. 2015

Published in Knowledge and Information Systems.

ModEx and Seed-Detective: Two novel techniques for high quality clustering by using good initial seeds in K-Means

By Anisur Rahman, Zahidul Islam, Terence Bossomaier. 2015

Published in Journal of King Saud University - Computer and Information Sciences.

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Creators

Tjen-Sien Lim

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