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Implementation of Logistic Regression on Diabetic Dataset using Train-Test-Split, K-Fold and Stratified K-Fold Approach

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Abstract

Diabetes is a chronic metabolic disorder causing high blood sugars, that further severely affect body parts like the heart, liver, kidneys, lungs, eyes, nerves, blood vessels etc. There are three types of diabetes- Type-1 Diabetes, Type-2 Diabetes, and Gestational Diabetes. In Type-1, body of the patient fails to produce insulin. In Type-2 diabetes, cells of the body fails to respond to insulin effectively. Gestational diabetes occurs during pregnancy. There are many approaches used to analyse this disease. We have used the Machine learning approach for analysing diabetes. We have used 768 records from “pima diabetes dataset”. In this paper, we have used Logistic regression with Train Test Split, K-Fold cross-validation and Stratified K-Fold approach.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, India

    Meenu Bhagat & Brijesh Bakariya

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  1. Meenu Bhagat
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  2. Brijesh Bakariya
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Correspondence to Meenu Bhagat.

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Significance Statement: In this paper, the proposed approach analyses implementation of Train test Split, K-Fold, and Stratified K-Fold cross-validation techniques while using Logistic Regression on Diabetic Database.

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Bhagat, M., Bakariya, B. Implementation of Logistic Regression on Diabetic Dataset using Train-Test-Split, K-Fold and Stratified K-Fold Approach. Natl. Acad. Sci. Lett. 45, 401–404 (2022). https://doi.org/10.1007/s40009-022-01131-9

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  • DOI: https://doi.org/10.1007/s40009-022-01131-9

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