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Statistical Issues in Machine Learning Towards Reliable Split Selection and Variable Importance Measures (eBook, PDF)

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Recursive partitioning methods from machine learning are being widely applied in many scientific fields such as, e.g., genetics and bioinformatics. The present work is concerned with the two main problems that arise in recursive partitioning, instability and biased variable selection, from a statistical point of view. With respect to the first issue, instability, the entire scope of methods from standard classification trees over robustified classification trees and ensemble methods such as TWIX, bagging and random forests is covered in this work. While ensemble methods prove to be much m...

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