MUTE-Reco: MUTual Information Assisted Ensemble Feature RECOmmender System for Healthcare Prognosis

no code implementations • 28 Sep 2022 • Abhishek Dey, Debayan Goswami, Rahul Roy, Susmita Ghosh, Yu Shrike Zhang, Jonathan H. Chan

The performance of the proposed recommender is compared with four state-of-the-art methods using recommender systems' performance metrics like average precision@K, precision@K, recall@K, F1@K, reciprocal rank@K. Experimental results show that the model built with the recommended features can attain a higher accuracy (96. 6% and 98. 6% using support vector machine and neural network, respectively) for classifying different stages of ccRCC with a reduced feature set as compared to existing methods.

feature selection Recommendation Systems

Transfer-Recursive-Ensemble Learning for Multi-Day COVID-19 Prediction in India using Recurrent Neural Networks

no code implementations • 20 Aug 2021 • Debasrita Chakraborty, Debayan Goswami, Susmita Ghosh, Ashish Ghosh, Jonathan H. Chan

This method with two countries, Spain and Brazil, is seen to achieve the best performance amongst all the combinations as well as compared to other traditional regression models.

Ensemble Learning Transfer Learning