Information Systems Education Conference
ISECON Proceedings

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Workshop Presentation

Data Mining Methods Workshop Using R

Musa J Jafar
West Texas A&M University

Jeffry Stephen Babb
West Texas A&M University

Kareem Dana
West Texas A&M University

Objectives

Data Mining is the process of extracting valid, authentic and “ACTIONABLE” information from large data sets for the purpose of decision support. It is a combination of theories, practices and techniques from Machine learning, Statistics, Information Theory and Computer Science. In this workshop we will explore the underlying theoretical foundation of data mining algorithms. We will also provide hands-on model building and prediction tutorials for supervised learning algorithms such as Decision Trees, Neural Networks, Na├»ve Bayes algorithms and unsupervised learning algorithms such as clusters Analysis. We will Use R and R Libraries to perform the Data Mining tasks. Participants who would like to actively participate in the hands-on part of the workshop should load the latest release of R on-to their Machines.

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Targeted Attendees
IS faculty currently teaching, or desiring to teaching, a senior-level and/or graduate-level course in data mining methods. Alternatively, anyone interested in the topic is also welcome.

Recommended Citation: Jafar, M. J., Babb, J. S., Dana, K., (2012). The Proceedings of the Information Systems Education Conference, v.29 n.2062, New Orleans, LA.