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Chinese translation for "linear classifier"

线性分类器

Related Translations:
sludge classifier:  除泥分级器
structured classifier:  结构化类元
consenco classifier:  自动卸载式干涉沉降分级机
fahrenwald classifier:  法伦瓦德式分级机
cascade classifier:  梯级式分选机
classifier fan:  分级机风扇
classifier tank:  分级槽分级箱
table classifier:  淘汰盘, 摇床摇床用的分级机
tank classifier:  槽式分级机
duplex classifier:  双重分粒器
Example Sentences:
1.There are many conventional classifiers , which are generally divided into two categories : linear classifiers and nonlinear ones
分类器一般分为线性分类器和非线性分类器。
2.The operating object of all these linear classifiers is vector pattern , i . e . , before applying them , any non - vector pattern should be firstly vectorized into a vector pattern
然而现有的线性分类器几乎都是针对向量模式的,即所有的模式都采用向量表示,要应用于矩阵表示的模式,必须首先将矩阵模式转换成向量模式。
3.These three classifiers are a linear classifier based on fuzzy features , a hierarchy classifier based on features of geometry definitions and a distance classifier based on frequency features of stroke curvature
使用的分类器分别为基于模糊特征的线性分类器、使用几何定义特征的分层分类器以及基于曲度频域特征的距离分类器。
4.Classifier is an important ingredient in pattern recognition . among all the classifiers , linear classifiers are paid great attention in statistical pattern recognition due to their simplicity and easy expansibility to nonlinear classifiers
在模式识别系统中,分类器是一个重要的组成部分,分类器设计的好坏将直接影响模式识别系统最终的识别性能。
5.The comparative performances are studied among the nmfs + rbf method , the pca + rbf method , and the pca + fld ( fisher ' s linear discriminant ) method . all simulations are carried out on the orl face database . the simulation results show that rbf classifier outperforms k - nearest neighbor linear classifier significantly in recognizing faces with occlusions , and the holistic representations are generally less sensitive to occlusions or noise than parts - based representations
为了验证本文所提出的nmfs + rbf算法的性能,经典的基于pca和fisher线性判别( fisher ' slineardiscriminant , fld )的人脸识别方法,以及基于pca和rbf的人脸识别方法,被用于和本文所提出的人脸识别方法进行比较。
6.Radial basis function ( rbf ) neural networks , which can be used as non - linear classifiers , have been applied extensively in pattern classification because of their salient features in being universal approximators , possing the best approximation property and the fast learning speed and having more compact topology than other neural networks
径向基( radialbasisfunction , rbf )神经网络分类器,作为非线性分类器,具有全局函数逼近、函数拟合度好、收敛速度快、网络结构紧凑等优点,被广泛运用于模式识别问题中。
7.Svm method is presented on the condition of linear classifier , and has been developed as an effective way in solving problems of nonlinear pattern recognition . in consideration that the problem of classification existing in reality is always nonlinear , and unable to be separated completely , a minute explanation of c - support vector classification ( c - svc ) is given and - support vector classification ( - svc ) - - a method for improvement in which parameter has objective significance is also introduced to avoid the disadvantage that parameter c in c - svc is of no exact significance
支持向量机是从线性可分的分类情况下提出的,并发展成用来解决非线性模式识别问题的有效手段,由于现实中存在的分类问题往往是非线性的,且可能无法完全分开,文中主要介绍了用于处理此类问题的非线性软间隔分类机,即c -支持向量分类机,并介绍了一种改进的方法: -支持向量分类机,其参数具有一些直观上的意义,避免了c -支持向量分类机中参数c没有确切意义的缺点。
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