Applying Data Mining Techniques using SAS® Enterprise Miner^TM 4.3

Duration

3 days

Description

This course is designed for data analysts and qualitative experts who want a general understanding of data mining. It provides extensive hands-on experience with Enterprise Miner 4.3 and covers the basic skills required to assemble analyses.

Prerequisite Skills

Before attending this course, you should have:

• An understanding of statistics. This knowledge can be gained by attending an introductory statistics course, for example: Applying Statistical Concepts using SAS or Applying Statistical Concepts using SAS Enterprise Guide
• Experience of writing SAS code and manipulating SAS data sets. This can be gained by attending a SAS Essentials: An Introduction to SAS Programming course.

SAS Modules Used

This course is available for both SAS Enterprise Miner 4 and 5 users.
Please contact us for more information.

Course Topics

Introduction to Data Mining

• history of data mining
• data mining and its uses
• introduction to the SEMMA process.

Predictive Modelling Using Decision Trees

• introduction to SAS Enterprise Miner
• modelling issues and data difficulties
• introduction to decision trees
• building and interpreting decision trees.

Predictive Modelling Using Logistic Regression

• introduction to logistic regression
• performing logistic regression in

SAS Enterprise Miner.

Variable Selection

• exploring a number of variable selection methods in SAS Enterprise Miner.

Predictive Modelling using Neural Networks

• introduction to neural networks
• visualising neural networks.

Model Evaluation and Implementation

• model evaluation: comparing candidate models
• ensemble models
• model implementation: generating and using score code.

Cluster Analysis

• K-means cluster analysis
• self-organising maps (EM4 course only).

Association and Sequence Analysis

• introduction to association analysis
• interpretation of association and sequence analysis
• dissociation analysis.