Jordon Hudson, Kash Patel and MJ’s fax machine: Pablo Torre’s ‘terminal content brain’ battles the algorithm Zak Keefer May 30, 2025 ...

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML ...

Support Vector Machines (SVM), a supervised learning algorithm, are particularly effective in this domain due to their ability to classify data and perform regression tasks with high precision [1].

In order to ensure the safe operation of trains, an improved whale optimization algorithm is proposed to optimize the rail corrugation evolution trend prediction model of the least squares support ...

About this issue Abstract To solve the problem of difficult quantitative identification of surface defect depth during laser ultrasonic inspection, a support vector machine-based method for ...

This approach utilizes the Cleveland dataset by combining the Artificial Flora Optimization algorithm with the Support Vector Machine. The proposed algorithm functions as a meticulous gardener, ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

The Support Vector methods was proposed by V.Vapnik in 1965, when he was trying to solve problems in pattern recognition. In 1971, Kimeldorf proposed a method of constructing kernel space based on ...

A performance evaluation of random forest, artificial neural network, and support vector machine learning algorithms to predict spatio-temporal land use-land cover dynamics: a case from lusaka and ...