New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...
IEEE

Bayesian Classification of Hyperspectral Imagery Based on Probabilistic Sparse Representation and Markov Random Field

Abstract: This letter presents a Bayesian method for hyperspectral image classification based on the sparse representation (SR) of spectral information and the Markov random field modeling of spatial ...
IEEE

A Bayesian Meta-Learning-Based Method for Few-Shot Hyperspectral Image Classification

Abstract: Few-shot learning provides a new way to solve the problem of insufficient training samples in hyperspectral classification. It can implement reliable classification under several training ...
Visual Studio Magazine

Multinomial Naive Bayes Classification Using the scikit Library

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 ...
Visual Studio Magazine

Naive Bayes Classification Using C#

Notice that all the data values are categorical (non-numeric). This is a key characteristic of the naive Bayes classification technique presented in this article . If you have numeric data, such as a ...
Frontiers

Beating Naive Bayes at Taxonomic Classification of 16S rRNA Gene Sequences

Naive Bayes classifiers (NBC) have dominated the field of taxonomic classification of amplicon sequences for over a decade. Apart from having runtime requirements that allow them to be trained and ...
Frontiers

An Explainable Bayesian Decision Tree Algorithm

Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...