Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are st

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to p

xMCA | Maximum Covariance Analysis in Python The aim of this package is to provide a flexible tool for the climate science community to perform Maximu

Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that