Classification model for predicting whether a patient is at risk of death during hospitalization
-
Updated
Apr 24, 2024 - Jupyter Notebook
Classification model for predicting whether a patient is at risk of death during hospitalization
This repository contains all program files and datasets used in implementation of Masters Thesis Research Work for the topic - "Efficient Clustering via Kernel Principal Component Analysis and Optimal One Dimensional Clustering".
My Machine Learning course projects
Projects for MSc course: Computational Intelligence and Statistical Learning
First Advanced Numerical Methods
Advanced Numerical Methods Project: Face Recognition
LINMA2472: Algorithms in Data Science
KPCA and LDA implementations.
cReddit: Misinformation Assessment Tool for Comments from Reddit
Anomaly detection on a production line using principal component analysis (PCA) and kernel principal component analysis (KPCA) *from scratch*.
A mathematical analysis and implementation of kernel PCA 🤖
Data science Mini projects
Application of PCA and KPCA algorithms to perform dimensionality reduction on the set of parameters in LPV models
[IEEE TCYB 2021] Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network
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…
MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).
Add a description, image, and links to the kpca topic page so that developers can more easily learn about it.
To associate your repository with the kpca topic, visit your repo's landing page and select "manage topics."