| 1. | Minimum distance classifier is a simple and effective classification method
摘要最小距离分类器是一种简单而有效的分类方法。 |
| 2. | In the process of classification , use minimum distance classifier to obtain recognition results
在识别阶段本文使用了最小距离分类器对待识别人脸进行了分类。 |
| 3. | On the basis of analyzing the classification principle of decision tree classifier and parallelpiped classifier , a new classification method based on normalized euclidian distance , called wmdc ( weighted minimum distance classifier ) , was proposed
通过分析多重限制分类器和决策树分类器的分类原则，提出了基于标准化欧式距离的加权最小距离分类器。 |
| 4. | In the course of classifiers design , considering that the single classifier has not high recognition rate , we construct a combining classifier with a minimum distance classifier and a fuzzy nn classifier to improve the recognition rate
在分类器设计过程中，考虑到单一分类器的识别率不是很高，本文将最小距离分类器与模糊神经网络分类器结合起来构成一个组合分类器，以期提高人脸识别率。 |
| 5. | Aiming at these problems , the proposed network integration method is improved . three minimum distance classifiers , which extract different local features , are proposed and they are combined to form an integration system by making use of the above methods
针对这些问题，本文对所提出的网络集成方法进行了改进，给出了三个提取不同局部特征的最小距离分类器，并采用上述方法构成了集成型识别系统。 |
| 6. | By adding weight define with nominal and string attributes and adding range restriction of attribute ' s value , wmdc extended applicability of mdc ( minimum distance classifier ) using normalized euclidian distance and improved its classification accuracy
该分类器通过对标称型和字符串型属性的距离的加权定义，以及增加属性值的范围约束，扩大了最小标准化欧式距离分类器的适用范围，同时提高了其分类准确率。 |
| 7. | In the course of classifiers design , this paper recognizes human face with a minimum distance classifier . the similitude of two face image is calculated out by means of distance formulate , and proper threshold is selected to judge whether the two face images belong to one person
在分类器设计过程中，采用最小距离分类器的分类方法进行判断识别，利用距离公式度量两幅人脸图像的相似程度，并选取合适的阈值进行判断识别。 |
