Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

While exploring one of the most infamous crimes of the past decade, Johnny Berchtold was committed to bringing a full spectrum of emotion to his portrayal of Paul Murdaugh. The Murdaugh: Death in the ...

Oscar winner Jamie Lee Curtis opened up about her considerations of retirement and Hollywood’s aging problem in relation to her parents, icons of the industry Janet Leigh and Tony Curtis. In an ...

This model was trained and tested on a 70%/30% split (train/test result cohort), achieving an area under the receiver operator curve on the test set of 0.866 (95% CI, 0.857 to 0.875). Assigning a ...

The hottest trend on the horizon for artificial intelligence (AI) is agentic AI, according to Jason Moore, Ph.D., chair of the Department of Computational Biomedicine at Cedars-Sinai. Unlike ...

Reinforcement learning (RL) trains agents to make sequential decisions by maximizing cumulative rewards. It has diverse applications, including robotics, gaming, and automation, where agents interact ...