linear classifier中文是什么意思

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中文翻译
造句

线性分类器

linear adj. 1.线的，直线的。 2.长度的。 3.【数学】 ...
classifier n. 1.分类者。 2.【矿物】分级机。 3.【化学】 ...
piecewise linear classifier 分段线性分类器
classifier n. 1.分类者。 2.【矿物】分级机。 3.【化学】分粒器。 4.(汉语等中的)量词。
be linear with 与...成线性关系
linear adj. 1.线的，直线的。 2.长度的。 3.【数学】一次的，线性的。 4.【动、植】线状的；细长的。 5.由线条组成的，以线条为主的，强调线条的。 linear amplification 直线放大。 a linear equation 一次方程式。 a linear leaf 线形叶。 linear arts 线条艺术。
linear a 线形文字a; 线性文字a
no-linear 非线性的
adaptive classifier 自适应分类器
air classifier 风力分级器; 风力化级器; 风筛; 空气分级机; 空气分级器; 空气过滤器; 气力分级器; 气流分级机
akins classifier 阿金斯分级机; 螺旋分级机
annular classifier 环式分级机
array classifier 阵列分类器
atkins classifier 阿特金斯选粒机
automatic classifier 自动分类机
bayes classifier 贝斯分类符; 贝叶斯分类器
bayesian classifier 贝叶斯分类器
bowl classifier 分级槽; 浮槽分级机; 浮槽分级器; 浮槽式分级机
cascade classifier 梯级式分选机
centrifugal classifier 离心分级机; 离心分级器
classifier fan 分级机风扇
classifier gate 分选器挡板
classifier overflow 分级机溢流
classifier role 类元角色; 元角色
classifier separator 分级机式分选机; 分级选矿机; 重力式粗粉分离

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例句与用法

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。
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。
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。
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。
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。
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。
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。

百科解释

In the field of machine learning, the goal of statistical classification is to use an object's characteristics to identify which class (or group) it belongs to. A linear classifier achieves this by making a classification decision based on the value of a linear combination of the characteristics.

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Last modified time:Mon, 18 Aug 2025 00:29:56 GMT