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_5

5. Miscellaneous Resampling Techniques

Timothy Masters¹ 

(1)

Ithaca, New York, USA

 

• Bagging

• AdaBoost

• Comparing the Boosting Algorithms

• Permutation Training and Testing

Previous chapters explored some uses for resampling techniques. In Chapter 3 we saw that the bias and variance of parameter estimators could themselves be estimated. This included model parameters as well as performance measures based on independent test data. Then in Chapter 4 we saw that performance measures for a model could be safely obtained from the very same data that was used to train the model. In this chapter we will explore assorted methods for ...