Predicting the Contraceptive Method Choice of a Woman Based on Demographic and Socio-economic Characteristics

The objective of this study is to predict the contraceptive methods (no use, long-term methods, or short-term methods) of a woman based on her demographic and socio-economic characteristics. A data-set of 1473 married women with their demographic and socio-economic characteristics used in this study. The Source for the data-set is the UCI Machine Learning Repository at, http://http://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice. This study consists of two phases. The objective of Phase I is to preprocess and explore the data-set in order to build the model in Phase II. All the activities have been performed in the Python package in this study and Compiled from Jupyter Notebook This report covers both narratives and the Python pseudo-codes for the data preprocessing and exploration performed under phase I. Content of this report is organized as follows. Section 1 describes the data sets and their attributes. Section 2 covers data preprocessing. In Section 3, each attribute and its inter-relationships are explored.

Source for the Data-set:

https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice

Phase I:

Preprocessing and exploring the data-set in order to build the model in Phase II

data-set: Data_Set.csv

Python Code: Phase1.ipynb

Report: s3400652_MATH2319_Phase1 Report.pdf

Phase II:

Building a model that predicts the contraceptive method

data-set: Preprocessed_Data.csv

Python Code: Phase2.ipynb

Report: s3400652_MATH2319_Phase2 Report.pdf