Assessing and Improving Prediction and Classification: Theory and Algorithms in C++

© Timothy Masters 2018

Timothy MastersAssessing and Improving Prediction and Classificationhttps://doi.org/10.1007/978-1-4842-3336-8_2

2. Assessment of Class Predictions

Timothy Masters¹ 

(1)

Ithaca, New York, USA

 

• The Confusion Matrix

• ROC (Receiver Operating Characteristic) Curves

• Optimizing ROC-Based Statistics

• Confidence in Classification Decisions

• Confidence Intervals for Future Performance

The previous chapter focused on models that make numeric predictions. This chapter deals with models whose goal is classification. It must be understood that the distinction is not always clear. In particular, almost no models can be considered to be pure classifiers. Most classification models make a numeric prediction (of a scalar or a vector) and then use this ...