Pattern Recognition, Statistical
Pattern Recognition, Statistical
复制标题
模式识别，统计
DOI：
10.1002/0470018860.s00013
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Thomas Hofmann
中科院分区：
文献类型：
--
作者：
Thomas Hofmann
统计模式识别处理自动将对象分类为属于一组可能类别中的一个或多个类别的问题。对象通常由原始数据表示，原始数据可能包括测量的或已知的对象属性，并总结在特征向量中。总体目标是基于具有已知类别成员资格的对象训练集来推断合适的分类规则，将特征向量映射到类别标签。
Statistical pattern recognition deals with the problem of automatically classifying objects as belonging to one or more classes from a set of possible classes. Objects are typically represented by raw data that may include measured or known object properties and which are summarized in a feature vector. The general goal is to infer suitable classification rules that map feature vectors to class labels based on a training set of objects with known class memberships.