Lecture

Decision Forests: Structure and Training

In course

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Description

This lecture covers the fundamentals of decision forests, focusing on decision trees, training processes, weak learners, entropy, information gain, and the transition from trees to forests. It also discusses boosting, 3D pose estimation, body part recognition, and the practical applications of decision forests.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_xl5zb9z2

About this result

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Ontological neighbourhood

Information engineering

Machine learning: Decision tree learning

Physics

Thermodynamics: Statistical mechanics

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