Diet Recommendation System Using K-Means Clustering Algorithm of Machine Learning

Nidhi Waghela; Jahanvi Mistry; Melony Bharucha; Ms. Monali Parikh

doi:10.32628/CSEIT2410445

Authors

Nidhi Waghela Research Scholar, Institute of Information Technology, Krishna School of Emerging Technology & Applied Research, KPGU University, Varnama, Vadodara, Gujarat, India Author
Jahanvi Mistry Research Scholar, Institute of Information Technology, Krishna School of Emerging Technology & Applied Research, KPGU University, Varnama, Vadodara, Gujarat, India Author
Melony Bharucha Research Scholar, Institute of Information Technology, Krishna School of Emerging Technology & Applied Research, KPGU University, Varnama, Vadodara, Gujarat, India Author
Ms. Monali Parikh Assistant Professor, Department of Information Technology and Engineering, Krishna School of Emerging Technology & Applied Research, KPGU University, Varnama, Vadodara, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT2410445

Keywords:

Diet Recommendation, Machine Learning, Clustering, Health Factors, Vegetarian and Non-Vegetarian

Abstract

In today’s world, many people suffer from range of illnesses due to lack of nutrients in their daily diet. It’s not always simple to recommend diet right away. The majority of individuals in the today’s world are fanatically trying to reduce weight, gain weight, or keep their health in check. The study relies on a database that has various amount of nutrients. As a result of the circumstance, we set out to create a program that would help out individuals to become healthy. Only three orts of good are recommended weight loss, weight gain, and staying healthy. The diet recommendation system leverages the user input such as, name, age, height, weight which calculate BMI and provide necessary diet based on the option of vegetarian or non-vegetarian meals from three categories which are weight gain, weight loss, and staying healthy. We’ll discuss about the classification of food based on machine learning in this post. This research includes K-means Clustering algorithm for future diet plan prediction.

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References

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