Identifying Disease and Diagnosis in Females Using Machine Learning

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Author(s): Sabyasachi Pramanik (Haldia Institute of Technology, India)and Samir Kumar Bandyopadhyay (Bhawanipore Educational Society, India)
Copyright: 2023
Pages: 24
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch187

Keywords: Data Analysis and Statistics / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Here, the researchers are trying to prepare a model for identifying whether a patient is diabetic or not. The Pima Indian Dataset has been used in this case study. There are two types of diabetes. The research consists of two stages. The first is data pre-processing, and the other is classifier construction. After pre-processing, the data classifier will be constructed which will predict whether the patient is diabetic or not. Here the researchers plan to use decision tree classifier and random tree classifier. After studying the dataset, the researchers handled the missing values in optimum ways. All the types of proposed algorithm have been described in this article.

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Identifying Disease and Diagnosis in Females Using Machine Learning

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