Incremental PCA. Cheese Shop : MDP 2.1. MDP is a Python data processing framework.
Implemented algorithms include: Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis, Independent Slow Feature Analysis, and many more. Latest Version: 3.3 Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP consists of a collection of trainable supervised and unsupervised algorithms or other data processing units (nodes) that can be combined into data processing flows. Common Sense Computing Initiative. PCA Module. Contents 1.
Introduction Implementation of a PCA module in python using numpy, scipy and python extensions (here, in C). The module carries out Principal Component Analysis (PCA) using either Singular Value Decomposition (SVD) or the NIPALS algorithm. Solem's vision blog: PCA for Images using Python. I've looked around for a nice and clean implementation of principal component analysis in python but couldn't really find anything that fits.
PCA Module looks useful but seems like a lot of stuff for something this simple. So anyway, I decided to spend part of my Monday evening writing a simple implementation. Numpy - Principal component analysis in Python.