Abstract: In recent years, deep learning models have been widely used for hyperspectral image (HSI) classification, and most of the existing deep-learning-based methods merely focused on high ...
Near-infrared (NIR) spectroscopy is a promising tool for optimizing seed analyses quickly and assertively. The aim of this study was to investigate the viability of NIR in association with chemometric ...
Abstract: This paper presents a new spectral-spatial classification method for hyperspectral (HS) images. The proposed method is based on integrating hierarchical segmentation results into Markov ...
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 ...
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 ...
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 ...
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 ...