Food Classification using Machine Learning Algorithms

DOI

10.2991/978-94-6463-858-5_86How to use a DOI?

Keywords

Bidirectional Encoder Representations from Transformers (BERT); K-Nearest Neighbors (KNN); Naive Bayes (NB); Food Classification; Machine Learning

Abstract

In an era of increasingly complex food production, diversified preferences, and dietary restrictions, consumers want accurate information on food classification to help them make informed food decisions. The paper presents an all-rounded system using machine learning to classify foods into vegetarian, vegan, non-vegetarian, and Jain categories. We used the Open Food Facts dataset for multiple machine learning techniques, including K-Nearest Neighbor(KNN), Naive Bayes(NB) and Bidirectional Encoder Representations from Transformers(BERT). The text preprocessing steps, including normalization and lemmatization, improved the quality and accuracy of the models. Our results depict that NB model achieved a balanced performance with 73.9% accuracy, while the KNN model showed high reliability in identifying categories like vegetarian and vegan at 82.05% accuracy. However, the BERT model not performed well with Jain food classification due to class imbalance. This paper highlights the use of machine learning algorithms to enhance the transparency and personalization aspect of food classification to improve the customer’s decision toward nutritional choice.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Aditi Ahuja
AU  - Vrudhi Kedia
AU  - Mahvish Ansari
AU  - Bhavya Grover
AU  - Shubha Puthran
PY  - 2025
DA  - 2025/11/04
TI  - Food Classification using Machine Learning Algorithms
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1034
EP  - 1046
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_86
DO  - 10.2991/978-94-6463-858-5_86
ID  - Ahuja2025
ER  -