Minimum distance classifier is a simple and effective classification method 摘要最小距離分類器是一種簡單而有效的分類方法。
In the process of classification , use minimum distance classifier to obtain recognition results 在識別階段本文使用了最小距離分類器對待識別人臉進行了分類。
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 通過分析多重限制分類器和決策樹分類器的分類原則,提出了基于標準化歐式距離的加權最小距離分類器。
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 在分類器設計過程中,考慮到單一分類器的識別率不是很高,本文將最小距離分類器與模糊神經網絡分類器結合起來構成一個組合分類器,以期提高人臉識別率。
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 針對這些問題,本文對所提出的網絡集成方法進行了改進,給出了三個提取不同局部特征的最小距離分類器,并采用上述方法構成了集成型識別系統(tǒng)。