Year: 1996
Type: dissertation
Abstract: Decision tree learning is an important field of machine learning.In this study we examine both formal and practical aspects of decision tree learning.We aim at answering to two important needs: The need for better motivated decision tree learners and an environment facilitating experimentation with inductive learning algorithms.As results we obtain new Computing Reviews (1991)
Source: Työväentutkimus Vuosikirja
Author: Tapio Elomaa
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Helsingin Yliopisto
OpenAlex ID: W1507857655