Feature Engineering Studio Special Session September 25, 2013.

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Presentation transcript:

Feature Engineering Studio Special 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?