November 2014
Beginner to intermediate
446 pages
12h 16m
English
Content preview from Predictive Analytics and Data MiningBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 8
Model Evaluation
Abstract
This chapter describes three commonly used tools for evaluating the performance of a classification algorithm. We first introduce the confusion matrix and provide the definitions for several terms that are used in conjunction, such as sensitivity, specificity, recall, etc. We then describe how to construct receiver operating characteristic (ROC) curves and show when it would be appropriate to use them along with the area under the curve (AUC) concept. Finally we present lift and gain charts, and show how to construct and interpret them. The RapidMiner implementation includes step-by-step processes for building each of these three very useful evaluation tools.
Keywords
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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