文件名称:LearningPatternClassificationASurvey
- 所属分类:
- 人工智能/神经网络/遗传算法
- 资源属性:
- [PDF]
- 上传时间:
- 2012-11-26
- 文件大小:
- 802kb
- 下载次数:
- 0次
- 提 供 者:
- 蒋**
- 相关连接:
- 无
- 下载说明:
- 别用迅雷下载,失败请重下,重下不扣分!
介绍说明--下载内容均来自于网络,请自行研究使用
模式识别学习综述.该论文的英文参考文献为303篇.很有可读价值.Abstract— Classical and recent results in statistical pattern
recognition and learning theory are reviewed in a two-class
pattern classification setting. This basic model best illustrates
intuition and analysis techniques while still containing the essential
features and serving as a prototype for many applications.
Topics discussed include nearest neighbor, kernel, and histogram
methods, Vapnik–Chervonenkis theory, and neural networks. The
presentation and the large (thogh nonexhaustive) list of references
is geared to provide a useful overview of this field for both
specialists and nonspecialists.-Summary of pattern recognition learning. The paper for English 303 references. Very readable value. Abstract-Classical and recent results in statistical patternrecognition and learning theory are reviewed in a two-classpattern classification setting. This basic model best illustratesintuition and analysis techniques while still containing the essentialfeatures and serving as a prototype for many applications.Topics discussed include nearest neighbor, kernel, and histogrammethods, Vapnik-Chervonenkis theory, and neural networks. Thepresentation and the large (thogh nonexhaustive) list of referencesis geared to provide a useful overview of this field for bothspecialists and nonspecialists.
recognition and learning theory are reviewed in a two-class
pattern classification setting. This basic model best illustrates
intuition and analysis techniques while still containing the essential
features and serving as a prototype for many applications.
Topics discussed include nearest neighbor, kernel, and histogram
methods, Vapnik–Chervonenkis theory, and neural networks. The
presentation and the large (thogh nonexhaustive) list of references
is geared to provide a useful overview of this field for both
specialists and nonspecialists.-Summary of pattern recognition learning. The paper for English 303 references. Very readable value. Abstract-Classical and recent results in statistical patternrecognition and learning theory are reviewed in a two-classpattern classification setting. This basic model best illustratesintuition and analysis techniques while still containing the essentialfeatures and serving as a prototype for many applications.Topics discussed include nearest neighbor, kernel, and histogrammethods, Vapnik-Chervonenkis theory, and neural networks. Thepresentation and the large (thogh nonexhaustive) list of referencesis geared to provide a useful overview of this field for bothspecialists and nonspecialists.
相关搜索: pattern
classification
pattern
recognition
模式识别
Nearest
Neighbor
Recognition
Classification-MatLab-Toolbox
Kernel
Methods
for
Pattern
Analysis
classification
pattern
recognition
模式识别
Nearest
Neighbor
Recognition
Classification-MatLab-Toolbox
Kernel
Methods
for
Pattern
Analysis
(系统自动生成,下载前可以参看下载内容)
下载文件列表
模式识别学习综述.pdf