Feature Engineering Studio Special Session

Feature Engineering StudioSpecial Session September 25, 2013

RapidMiner 5.3 • Data file and rapidminer xml file are on course webpage

Look at data

Look at process step-by-step

Build classifier

Goodness Criteria • Kappa • AUC (Warning!) • Accuracy (Warning!) • Precision • Recall

Turn cross-validation off

Other types of cross-validation • Student-level cross-validation • Population-level cross-validation • Content-level cross-validation • When you use these….

Setting up other types of cross-validation • BatchXValidation • SetRole

CompleteFeatureGeneration

RemoveCorrelatedFeatures

Other Classification Algorithms • W-J48 • W-JRip • W-KStar

Set up a Regression

Regression Algorithms • Linear Regression • W-RepTree • W-M5P • Neural Networks • Support Vector Machines

Goodness Criteria • Correlation • RMSE/MAD

Many other things RapidMiner can do… • These are just two types of common prediction models

For a broader overview of prediction modeling… • Come to next week’s special session

Questions? Concerns?

Feature Engineering Studio Special Session