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Computerized Pattern Recognition Applications to Chemical Analysis. Development of Interactive Feature Selection Methods for the K-Nearest Neighbor Technique.

机译：计算机模式识别在化学分析中的应用。 K-最近邻技术交互特征选择方法的发展。

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A systematic approach has been developed for feature selection in the application of the K-nearest neighbor (KNN) computerized pattern recognition method. The approach uses an operator-interactive computer system. A large number of potentially-useful features for classification of patterns can be screened for the most relevant members by a combination of recommended procedures. These include: (a) one-dimensional KNN classification of all patterns using each feature individually; (b) inspection of histogram displays of classification records for each feature;and (c) establishment of consensus classifications from combined one-dimensional results. A computerized trial-and-error procedure can then be implemented to find the best combination of a minimum number of features for accurate classification using the multi-dimensional KNN method. (Modified author abstract)

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pichler, marty a. perone,sam p.;
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年度 1974
页码 1-39
总页数 39
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
pattern recognition; chemical analysisinteractive graphics; classification; statistical analysis;

机译：模式识别;化学分析交互图形;分类;统计分析;

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专利

1. Application of K-Nearest Neighbor Rule in the Case of Intuitionistic Fuzzy Sets for Pattern Recognition [J] . Todorova L., Vassilev P. International Journal Bioautomation . 2009,第4期

机译：K最近邻规则在直觉模糊集模式识别中的应用
2. Fast Sign Recognition with Weighted Hybrid K-Nearest Neighbors Based on Holistic Features from Local Feature Descriptors [J] . Hu Zhaozheng, Li Bing, Hu Yuezhi Journal of Computing in Civil Engineering . 2017,第5期

机译：基于局部特征描述符整体特征的加权混合K最近邻快速符号识别
3. Simultaneous feature selection and feature weighting using Hybrid Tabu Search/K-nearest neighbor classifier [J] . Muhammad Atif Tahir, Ahmed Bouridane, Fatih Kurugollu Pattern recognition letters . 2007,第4期

机译：使用混合禁忌搜索/ K近邻分类器同时进行特征选择和特征加权
4. The Development of Interactive Feature Selection and GA Feature Selection Method for Emotion Recognition [C] . Kwee-Bo Sim, In-Hun Jang, Chang-Hyun Park International Conference on Knowledge-Based Intelligent Information and; International Conference on Knowledge-Based Intelligent Information and Engineering Systems(KES 2007); Italian Workshop on Neural Networks; 20070912-14; 20070912-14; Santiago de Com . 2007

机译：情感识别的交互式特征选择和遗传算法特征选择方法的发展
5. Development and application of pattern recognition and calibration methods for multivariate analytical chemical data. [D] . Egan, William Joseph. 1998

机译：多元分析化学数据的模式识别和校准方法的开发和应用。
6. A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications [O] . Jaime Vitola, Francesc Pozo, Diego A. Tibaduiza, 2017

机译：基于k-最近邻模式分类的传感器数据融合系统在结构健康监测中的应用
7. A New Feature Selection Method Based on K-Nearest Neighbor Approach [O] . Xianchang Wang, Lishi Zhang, Yonggang Ma 2017

机译：一种基于K-最近邻近方法的新特征选择方法
8. CHOICE:36 BAND FEATURE SELECTION SOFTWARE WITH APPLICATIONS TO MULTISPECTRAL PATTERN RECOGNITION [R] . W.C. JONES 1974

机译：选择：36波段特征选择软件，应用于多光谱模式识别

Computerized Pattern Recognition Applications to Chemical Analysis. Development of Interactive Feature Selection Methods for the K-Nearest Neighbor Technique.

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