Learning from potential disinformation introduces specific cognitive biases, causing individuals to systematically deviate from an idealized Bayesian updating strategy.

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...

Abstract: Because learning an optimal Bayesian network classifier is an NP-hard problem, learning-improved naive Bayes has attracted much attention from researchers. In this paper, we summarize the ...

In this blog post, I am going to teach you how to train a Bayesian deep learning classifier using Keras and tensorflow. Before diving into the specific training example, I will cover a few important ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

A full-code demo from Dr. James McCaffrey of Microsoft Research shows how to predict the type of a college course by analyzing grade counts for each type of course. General naive Bayes classification ...

Abstract: For a classification task, we usually select an appropriate classifier via model selection. How to evaluate whether the chosen classifier is optimal? One ...