Introduction to R for Data Mining

Presented:	Tuesday, June 5, 2012
Presenter:	Joseph Rickert, Technical Marketing Manager, Revolution Analytics
	Download the presentation, Rscripts and replay file.

We at Revolution Analytics are often asked “What is the best way to learn R?” While acknowledging that there may be as many effective learning styles as there are people we have identified three factors that greatly facilitate learning R. For a quick start:

Find a way of orienting yourself in the open source R world
Have a definite application area in mind
Set an initial goal of doing something useful and then build on it

In this webinar, we focus on data mining as the application area and show how anyone with just a basic knowledge of elementary data mining techniques can become immediately productive in R. We will:

Provide an orientation to R’s data mining resources
Show how to use the "point and click" open source data mining GUI, rattle, to perform the basic data mining functions of exploring and visualizing data, building classification models on training data sets, and using these models to classify new data.
Show the simple R commands to accomplish these same tasks without the GUI
Demonstrate how to build on these fundamental skills to gain further competence in R
Move away from using small test data sets and show with the same level of skill one could analyze some fairly large data sets with RevoScaleR

Data scientists and analysts using other statistical software as well as students who are new to data mining should come away with a plan for getting started with R.

Introduction to R for Data Mining

View more presentations from Revolution Analytics

About the Speaker

Joseph Rickert
Technical Marketing Manager
Revolution Analytics

Joseph is a marketing manager at Revolution Analytics with a passion for analyzing data and teaching people about R. He is a long-time Silicon Valley start-up guy having worked at a number of successful start-ups including Sytek, Alantec, Parallan Computer and Scotts-Valley Instruments. Joe holds graduate degrees in both the Humanities and Statistics. He taught statistics briefly at SJSU and is an occasional guest blogger at blog.revolutionanalytics.com.