Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

In a recent analysis, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and collaborator William Gilpin reported that one ...

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs ...

This study presents a valuable finding on how the locus coeruleus modulates the involvement of medial prefrontal cortex in set shifting using calcium imaging. The evidence supporting the claims was ...

Instead of training on a set of questions with fixed correct answers — which is what traditional supervised learning does — RFT uses a grader model to score multiple candidate responses per ...

A new study published in PLOS One introduces a large-scale method for detecting political bias in online news sources using ...

Abstract: We build an emotion recognition system based on Artificial Neural Network (ANN) and compare the same with the one based upon the Hidden Markov Modeling (HMM) scheme. Both the systems were ...