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Intelligent Refrigerator

  • Ishank AgarwalEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 910)

Abstract

In this research, models have been made to predict “Cuisines from Ingredients.” Many applications like prediction of top 100 cuisines based on mood and keeping in mind the health of the user, predicting similar dishes to the query dish, and comparison between optimized models on the basis of money loss that they incur if the food intake is not right are covered in this research. Formation of different patterns and combinations resulted when various machine learning models were applied to the given Yummly dataset of a wide variety of cuisines. These models provided a range of accuracies and the best one was used for each purpose according to the motto “survival of the fittest.”

Keywords

Multinomial naïve Bayes Logistic regression Random forest classifier K-nearest neighbors classifier K-fold cross-validation Sentiment classifier TF-IDF Linear regression Multiple regression Gradient descent Polynomial regression Ridge regression L2 penalty 

Notes

Acknowledgements

I would like to show our gratitude to Prof. Shikha Mehta and Prof. Prashant Kaushik for sharing their pearls of wisdom with me during the course of this project, and I hope to receive their continuous insights till the deployment of the project.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Jaypee Institute of Information Technology (JIIT)NoidaIndia

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