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Data Mining: Practical Tools and Techniques in R/Splus
Schedule
Location Start Date Duration Pre Register
Salt Lake City 8/26/2010 2 days Pre-Register
Seattle 8/26/2010 2 days Pre-Register
Data Mining: Practical Tools and Techniques in R/Splus
This course gives students an understanding of R/Splus tools used to investigate the main tasks that predictive analytics and exploratory data mining is usually called upon to accomplish and data preparation which is universally held as the key to successful data mining. We focus on the most common data mining tasks which are: Description, Estimation, Prediction, Classification, Clustering, Association and the need for Dimension Reduction with Principal Components and Factor Analysis. Analytical methods used in the class include decision trees, logistic regression, neural networks, link analysis (social networks) and Kernel-based Methods (SVMs).
Course Topics

Day 1

bulletOverview of R/S Systems and Data Mining
a. Data Preparation Tools in R/S
b. Handling Big Data in R/S
c. Drawing an uncontaminated input sample
d. Managing Exceptions and Extremes (outliers, missing values, etc)
e. Visualization Tools in R/S
bulletDimension Reduction Tools in R/S
a. Principal Components Analysis
b. Factor Analysis
c. Cluster Analysis

Day 2

bulletPredictive Analytics Tools in R/S
a. Decision Trees in R/S
b. Implementations of Classification Trees in R/S
c. Logistic Regression
d. Neural Networks tools in R/S
bulletSupervised Pattern Discovery with K-NN in R/S
bulletUnsupervised Clustering with K-Means in R/S
bulletSurvival Data Mining tools in R/S
bulletMiscellaneous Data Mining Techniques in R/S
a. Link Analysis (Social Network Analysis)
b. Random Forests
c. Kernel-based Methods (SVMs)
d. Genetic Algorithms
e. Association Rules
Course Format
This course consists of a series of short lectures with demonstrations and interactive sessions for the participants. Each student is provided with bound copies of the notes and a CD-ROM containing all example and exercises used on the course.
Duration and Prerequisites

Duration: 2 days

Before attending this course, you should have some basic computer experience:

bullet use a keyboard
bullet running software under windows and/or unix environment

Interested in our training? Please email the

Training Department
XLSolutions Corporation
sue@xlsolutions-corp.com
 
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