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Meeting	ACGS Committee Meeting 116 - Charlotte, NC - October 2015
Agenda Location	6 SUBCOMMITTEE C – AVIONICS AND SYSTEM INTEGRATION 6.1 BigData Machine Learning Using CrossCat
Title	BigData Machine Learning Using CrossCat
Presenter	Raman Mehra
Affiliation	Scientific Systems Company
Available Downloads*	presentation
	Downloads are available to members who are logged in and either Active* or attended this meeting.
Abstract	A revolution in Big Data Predictive Analytics has been created by the confluence of four major revolutionary technologies, viz. (i) availability of massive datasets, (ii) distributed cluster computing (iii) advances in non-parametric Bayesian Inference and (iv) Markov Chain Monte Carlo (MCMC) methods for fast probability calculations and stochastic searches in high dimensions. The paper presents a discussion of challenges in Big Data Analytics, followed by the presentation of a method for Automated Bayesian Machine Learning using a recently developed approach called CrossCat. This approach is based on non-parametric Bayesian Inference and efficient use of MCMC numerical algorithms. Under the DARPA XDATA program, SSCI, MIT and the University of Louisville have developed multiple interfaces for the CrossCat algorithm to facilitate the use of this sophisticated machine learning method in various applications by experts and non-experts alike.