An empirical comparison of supervised learning algorithms

Published: Jan 1, 2006
Abstract
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog Project in the early 90's. We present a large-scale empirical comparison between ten supervised learning methods: SVMs, neural nets, logistic regression, naive bayes, memory-based learning, random forests, decision trees, bagged trees, boosted trees, and boosted stumps....
Paper Details
Title
An empirical comparison of supervised learning algorithms
Published Date
Jan 1, 2006
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