Data Mining to Elicit Factors Causing Infertility in Women’s in Rural and Urban Areas

Mrs.Anamika Arora, Dr.Pradeep Chouksey

Abstract


In India each family had five to six children but from last decade’s low fertility is growing rapidly in both urban and rural areas of India. Economic and social modernization in India with gain in education, obesity and age led to lower fertility in every region of India. In this paper Data mining techniques like statistical analysis, classification, Naives bayes, J48 has been used to analyse and mine knowledge on significant factors causing infertility in women. Even though there are many factors were causing infertility in women, but only three factors Age, Obesity (BMI) and Education taken for analysis. Samples are taken from both rural and urban areas of Indore. Out of several independent attributes collected about outpatients, only three attributes consider to be significant have been taken up for preliminary study. The aim of the study is to assess both in the rural and urban areas they said factors in the light of fertility in women. Common attributes have been considered among an equal sample size of fertile and infertile outpatients of rural and urban areas. The result of the study shows that the attributes considered are significant in determining fertility of women both individually and together. In the research found that the education effects age of the marriage of women and age influence body mass index (BMI) and obesity triggers changes in hormonal levels which is the cause of the infertility in urban area’s whereas in rural area’s the percentage of infertility is low due to education and the age of the marriages is earlier compare to urban areas.

Keywords


Data mining, Statistical analysis, classification, Naive bayes, J48

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DOI: https://doi.org/10.26483/ijarcs.v8i5.4119

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