描述
主题包括数学回顾、贝叶斯决策理论、参数模式识别的最大似然与贝叶斯学习、非参数方法包括最近邻和线性判别。字符串、子串、子序列与树结构的句法识别。应用包括语音、形状与字符识别。
原文参考文本
Topics include a mathematical review, Bayes decision theory, maximum likelihood and Bayesian learning for parametric pattern recognition, non-parametric methods including nearest neighbor and linear discriminants. Syntactic recognition of strings, substrings, subsequences and tree structures. Applications include speech, shape and character recognition.
来源与参考
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来源参考 : https://calendar.carleton.ca/grad/courses/COMP/