Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of clas…

Implemented and evaluated four basic face recognition algorithms: Eigenfaces, Fisherfaces, Support Vector Machine (SVM), and Sparse Representation-based Classification (SRC) on YaleB dataset

LDA, KNN, GA, K-means on Iris, Sonar and USPS datasets.

Detection of Schizophrenia using Extreme Learning Machine

Medicon 2019 BCI competition

Analysis of PCA and LDA for CS: 551 Pattern Reconition course hw3

Exploiting Pose Dynamics for Human Recognition from Their Gait Signature

A New Support Vector Finder Method, Based on Triangular Calculations and K-means Clustering

This repository contains some basic machine learning codes for text analytics tool box in Matlab

pattern recognition projects

In this project I have extarcted 30 time and frequancy features from EEG signals (of left hand and right hand moving) in an espicific time window. Then using PCA i have decreased the features dimension to 10. Then I have quarried different methdos of ML: KNN(1,3,5,6), SVM(Linear kernel, Gaussian kernel), LDA, Naive bayes on different time windows.

Reconhecimento de Padrões: implementação de um classificador Bayesiano e uma classificador unidimensional baseado em limiar usando técnica de LDA

A MATLAB toolbox for supervised linear dimension reduction (SLDR) including LDA, HLDA, PLSDA, MMDA, HMMDA and SDA

A project of my course "Introduction to Pattern Recognition". Realize LDA using MATLAB.

Boiled egg problems (Solve with LDA, QDA, Naive Bayes Classifiers, decision tree, pruned decision tree)

Machine Learning Projects from Coursework