Affiliation:
1. Haldia Institute of Technology, India
2. Bhawanipore Educational Society, India
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.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Mapping Boundaries;Innovations, Securities, and Case Studies Across Healthcare, Business, and Technology;2024-04-12
2. Cloud Computing Applications in Biomedicine;Emerging Trends in Cloud Computing Analytics, Scalability, and Service Models;2024-03-22
3. AI-Decision Support System;Advances in Media, Entertainment, and the Arts;2024-01-10
4. Engineering, Geology, Climate, and Socioeconomic Aspects' Implications on Machine Learning-Dependent Water Pipe Collapse Prediction;Advances in Environmental Engineering and Green Technologies;2023-12-07
5. Application of Machine Learning Models for Early Detection and Accurate Classification of Type 2 Diabetes;Diagnostics;2023-07-15