Explorative multivariate statistics in Python
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Updated
Aug 25, 2021 - Python
Explorative multivariate statistics in Python
A Python 3 implementation of orthogonal projection to latent structures
R package plsdepot
Algorithmic framework for measuring feature importance, outlier detection, model applicability evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.
Implementation of a Partial Least Squares Regressor
R package for High dimensional data analysis and integration with O2PLS!
Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.
Correlation for African Soil between chemistry and fertility data using Logistic Regression. Treatment of infrared (FTIR) spectra by machine learning.
Fast CPU and GPU Python implementations of Improved Kernel PLS by Dayal and MacGregor (1997) and Shortcutting Cross-Validation by Engstrøm (2024).
This repository focuses on different linear regression methods which are uncommon.
Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.
PLS Lesson
Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."
📈 Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Specialized linear, polynomial (including equality constraints on points and slopes), multivariate and nonlinear regression/curve fitting functions.
Prediction of Miles per gallon (MPG) Using Cars Dataset
This project is aimed at predicting loan terms issued by World Bank to developing countries by using Regression, Decision Trees, K-Nearest Neighbors & PLSR in R
Python implementation of the paper "A study on wrist identification for forensic investigation" https://www.sciencedirect.com/science/article/abs/pii/S0262885619300733
An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM estimation in the multivariate context. Covariates can be grouped in themes.
Age estimation is performed from the facial images.
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