There are 1 repository under principal-components-regression topic.
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
Efficient non-linear PCA through kernel PCA with the Nyström method
Predicting solar generation based on weather forecast - a project which was part of Machine Learning course at BITS Pilani
Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."
This is a group project for MTH416A: Regression Analysis at IIT Kanpur
R packages which implements most known linear regression model: pls, OLS, ridge, lasso, LAR, principal components regression...
Model Selection Using PCR, PLSR, Best subsets, Ridge Regression and Lasso Regression
Machine Learning Project
Ejercicio de regresiones por distintos métodos (Mejor Selección de Conjuntos, Selección de pasos hacia adelante, Ridge, LASSO, Elastic Net, Componentes Principales, Mínimos Cuadrados Parciales, etc.)
Investigation of differences in the levels of development of the labour and employment field among the OECD member countries
This repository focuses on different linear regression methods which are uncommon.