Inductive, Evolutionary, and Neural Computing Techniques for Discrimination: A Comparative Study*
比较了多种机器学习方法在两组判别问题上的表现，使用模拟数据考察不同数据分布特征下的线性与非线性判别效果。
ABSTRACT This paper provides a comparative study of machine learning techniques for two‐group discrimination. Simulated data is used to examine how the different learning techniques perform with respect to certain data distribution characteristics. Both linear and nonlinear discrimination methods are considered. The data has been previously used in the comparative evaluation of a number of techniques and helps relate our findings across a range of discrimination techniques.