An interpretive machine learning model may be a feasible method for measuring agitation in dementia as well as in predicting ...

This repository contains Python scripts, shell scripts, gnuplot scripts, and datasets for performing Support Vector Machine classification. A Support Vector Machine (SVM) is a binary classification ...

Handwitten Digits USPS dataset has 7291 train and 2007 test images. The images are 16*16 grayscale pixels. The dataset is given in hdf5 file format, the hdf5 file has two groups train and test and ...

Abstract: Support vector machines (SVMs) are one of the most popular machine learning methods used to classify machine health conditions using the selected feature space. In machine fault detection ...

Shrestha, R. and Dave, R. (2025) Machine Learning for Identifying Harmful Online Behavior: A Cyberbullying Overview. Journal of Computer and Communications, 13, 26-40. doi: 10.4236/jcc.2025.131003 .

The following is a summary of “Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and ...

Support vector machines (SVMs) is a very popular machine learning technique, which has been successfully applied to many real-world classification problems from various domains. Despite of all its ...

This valuable study tests a methodology for the discovery of new honey bee-repellent odorants via machine learning. The conclusions of the study are supported by solid evidence, with predicted ...