Decision tree learning algorithms

Decision tree learning algorithms

This work is about analyzing decision tree algorithms and visualizing what is learnt as well as how the learning is done. After these analysis, a new model named Nested Decision Tree which composes classical decision trees with the soft decision tree model is proposed. C4.5, Linear Support Vector Machine, Multilayer Perceptron, Soft Decision Tree, Budding Tree and Nested Decision Tree are all implemented and studied.

Project Poster: 

Project Members: 

Fatih Doğan, Mert Can Çüçen

Project Advisor: 

Ethem Alpaydın

Project Status: 

Project Year: 

2015
  • Fall

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Department of Computer Engineering, Boğaziçi University,
34342 Bebek, Istanbul, Turkey

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