PML – Parallel Machine Learning
Overview
The Parallel Machine Learning (PML) Toolbox is a joint effort of the Machine Learning group at the IBM R&D Labs in Israel and the Data Analytics department at the IBM Watson Lab. The toolbox provides tools for execution of data mining and machine learning algorithms on multiple processor environments or on multiple threaded machines. The toolbox comprises two main components: an API for running the users' own machine learning algorithms, and several pre-programmed algorithms, which serve both as examples and for comparison. The pre-programmed algorithms include a parallel version of the Support Vector Machine (SVM) classifier, linear regression, transform regression, nearest neighbors, k-means, fuzzy k-means, kernel k-means, PCA, and kernel PCA.
Contact:
Amir Ronen (amirro@il.ibm.com)
Dorit Baras (doritb@il.ibm.com)