Machine Learning despite Unknown Classes

被引：0
|
作者：
Smith, Christopher B. [1 ]
机构：
[1] SW Res Inst, San Antonio, TX 78238 USA
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9 | 2009年
关键词：
Machine learning; multiclass machine learning;
D O I：
10.1109/ICSMC.2009.5346181
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper revisits supervised machine learning for multiclass problems with the assumption that all classes cannot be represented in a training set. This is common in many applications in which there are numerous classes or in which some classes are exceedingly rare. In this paper we propose the use of a decision function to serve in place of the decision boundaries which are used in many machine learning techniques. We demonstrate this technique using Fisher's iris data and an application to language recognition.
引用
收藏
页码：1861 / 1863
页数：3
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