Search Results for "pso-svm"

The Kaggle-EEG project is a machine learning solution developed for seizure prediction from EEG data, achieving 3rd place in the Kaggle/University of Melbourne Seizure Prediction competition. The repository processes EEG data to predict seizures by training machine learning models, specifically using SVM (Support Vector Machine) and RUS Boosted Tree ensemble models. The framework processes EEG data into features, trains models, and outputs predictions, handling temporal data to ensure accuracy.

Matlab code for the novel algorithms presented in the paper Convex formulation for radius-margin based Support Vector Machines

A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination.

Provides pre-compiled MEX functions that wrap around the libsvm C library. Many enhancement are applied to the C version of the library to speed up Matlab usage. 64-bit only.

mex-svm is a set of patches against SVM-Light to compile into "mex" libraries and enable fast Support Vector Machine evaluation from within MATLAB.

Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi

The simpleSVM project contains Machine Learning codes for algorithms based on the SimpleSVM. It provides methods for Support Vector Machines and related methods, such as One-Clas SVM, nu-SVM...