ItemConference Paper

Nutrition Analysis: A Data-Driven Approach for Optimizing Individual Dietary Choices

Title
Nutrition Analysis: A Data-Driven Approach for Optimizing Individual Dietary Choices
Creator
Chatterjee, Biswajit; Kumar, Tejas J.; Kokatnoor, Sujatha Arun; Kumar, Sandeep
Description
Maintaining good health, avoiding illnesses, and controlling ailments like diabetes, heart disease, and obesity all depend on proper diet. With the use of nutrition analysis, people can better understand their dietary requirements and choose foods that will support a healthy lifestyle. The goal of this studys data-driven approach to nutrition analysis is to maximize each persons dietary selections. Individualized recommendations are made for balanced nutrition by utilizing top-of-the-machine learning techniques to examine food patterns, nutrient consumption, and health effects. Food items are categorized based on their nutritional characteristics, and potential health effects are predicted using algorithms like Gradient Boosting, Multi-Layer Perceptron (MLP), Random Forest, Support Vector Classifier (SVC), Gaussian Nae Bayes (GNB), Decision Tree, Stochastic Gradient Descent (SGD), Linear Discriminant Analysis (LDA), and K-Nearest Neighbors (KNN). These models evaluated the relationship between dietary practices and nutritional needs. The final outcome is a comprehensive system that enables people to make knowledgeable food choices and optimize their nutrition in a way that promotes their overall health. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Source
Lecture Notes in Networks and Systems;Volume;1264 LNNS;pp.393-406
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Decision tree; Dietary optimization; Gaussian nae bayes (GNB); Gradient boosting; K-nearest neighbors (KNN); Linear discriminant analysis (LDA) and; Multi-layer perceptron (MLP); Nutrition analysis; Random forest; Stochastic gradient descent (SGD); Support vector classifier (SVC)
Coverage
Chatterjee B., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Kumar T.J., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India; Kumar S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981962178-1;
Format
online
Language
English
Type
Conference paper

Citation

Chatterjee, Biswajit; Kumar, Tejas J.; Kokatnoor, Sujatha Arun; Kumar, Sandeep, “Nutrition Analysis: A Data-Driven Approach for Optimizing Individual Dietary Choices,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25476.

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