Lecture

Decision and regression trees

In course

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Description

This lecture covers decision and regression trees, including the principles of tree predictors, impurity measures, empirical entropies, impurity decrease via a split, learning algorithms, and implementations. It also discusses conditional inference trees and tree pruning techniques.

Official source

https://mediaspace.epfl.ch/media/0_2mj78pko

About this result

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Information engineering

Machine learning: Decision tree learning

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