线性分类器的英文

• linear classifier

• "线性"英文翻译    linear; linearity
• "分类"英文翻译    classify
• "器"英文翻译    implement; utensil; ware
• "分段线性分类器" 英文翻译 :    piecewise linear classifier
• "线性分类" 英文翻译 :    linear classification; linear sort
• "分类器" 英文翻译 :    categorizer; cla ifier; classifier; grader; segregator; sorter
• "比较分类器" 英文翻译 :    comparator sorter
• "磁鼓分类器" 英文翻译 :    drum sorter
• "电子分类器" 英文翻译 :    electronic sorter
• "分类器设计" 英文翻译 :    categorizer design
• "分类器系统" 英文翻译 :    classifier system cs
• "复选分类器" 英文翻译 :    cs check sorter
• "光电分类器" 英文翻译 :    photoelectric sorter
• "横向分类器" 英文翻译 :    horizontal sorter
• "可视分类器" 英文翻译 :    visual bander
• "临督分类器" 英文翻译 :    supervised classifier
• "流动分类器" 英文翻译 :    flow sorter
• "裸片分类器" 英文翻译 :    die sorter
• "模式分类器" 英文翻译 :    pattern classifier
• "射流分类器" 英文翻译 :    fluid sorter
• "时间分类器" 英文翻译 :    time sorter
• "树状分类器" 英文翻译 :    tree classifier
• "统计分类器" 英文翻译 :    statistical sorter
• "细胞分类器" 英文翻译 :    cell sorters
• "相关分类器" 英文翻译 :    correlation classifier

• 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。
• In the project we process the data with the methods of smooth filter , boundary division technique and fisher linear sorting method
  算法上采用了平滑滤波技术,边界分割技术和交遇区方法设计fisher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。
• Secondly , in the different level of pattern recognition , we realize feature - level fusion based on neural network and score - level fusion based on multi - classifier . thirdly , some opinions about application of multi - biometrics are given and corresponding prototype systems are realized
  二、依据模式识别的不同层次，分别实现了特征层的整合和分数层的整合，特征层整合采用了神经网络方法，分数层整合采用了多层线性分类器方法。
• Through the theory of light radiation and intensity , we can use the fewest leds to satisfy the luminous intensity demand . through image segmentation theory , we can accurately pick module up from the test stripe when it is put in wrong directions . through image processing theory , we can acquire correct information and avoid the bad effects from the asymmetric chemistry reaction and instability of the devices
  用光的辐射和强度理论,我们计算出了获得足够图像强度所需的最少光源;用图像分割理论,我们在试纸条倾斜放置或有垂直方向上的偏移时,准确地提取出了各模块的数据;用平滑滤波和均值滤波理论,我们滤除了由于反应不均匀及硬件设备不稳定带来的噪声;用交遇区设计线性分类器的方法,我们降低了有限样本设计线性分类器带来的误差,提高了检验准确度。
• Main works based on the newspaper samples is just as the following : ( 1 ) texture block is designed to embody more font characters . ( 2 ) filter orientation is optimized with genetic algorithm to make the angle set subtler . then the multi - channel gabor filter may extract better features
  通过对实际字体样本的分析，本文主要完成了以下工作： ( 1 )设计了更能体现字体特征的纹理图像块； ( 2 )利用遗传算法对滤波角度进行了优化选择，得到了更为精细的角度集合，以此生成的多通道gabor滤波器能够提取稳定的字体特征； ( 3 )字体样本的分布具有多峰性质，以动态聚类算法得到的分段线性分类器更好地分类字体。
• But , such a vectorization will bring at least three potential problems : 1 ) structural or local contextual infor mation may be broken down ; 2 ) the higher the dimension of input pattern , the more me mory space are needed for the weight vector related to a classifier ; 3 ) when the dimension of a vector pattern is very high and while the sample size is small , it is easy to be overtrained
  如此转换至少会带来三个不足: 1 )空间或结构信息可能会遭到破坏; 2 )由于权向量的维数等于输入模式的维数,当输入模式维数很大时,权值的存储空间相应的会很大; 3 )对于大维数的向量模式,当样本数不多的时候,利用线性分类器易导致过拟合。
• Perceptron , relaxation , mse and ho - kashyap ( hk ) algorithm . hk is not robust to outliers . the modified hk with square approximation of the misclassification errors ( mhks ) tries to avoid this shortcoming and adopts similar principle to the support vector machine to maximize the separation margin
  线性分类器因其简单、易于分析和实现且容易推广为非线性分类器的优点而成为模式分类最常用的分类器,并产生了感知器( perceptron ) 、松弛算法( relaxation ) 、最小平方误差( minimumsquareerror , mse )和ho - kashyap ( h - k )算法等经典算法。
• In this paper , inspired by the method of feature extraction directly based on matrix patterns and the advantage of mhks , we develop a new mhks classifier based on matrix patterns ( matmhks ) . the method can mitigate the above shortcomings . we also make a further try of applying the algorithm proposed above to breast cancer detection
  受到已有面向矩阵的特征提取方法的启发,本文将此方法引入到正则化h - k线性分类器的设计中,设计出面向矩阵模式的双边正则化h - k分类算法matmhks ,克服了以上不足,并继承了mhks算法的优点。

• 线性分类器的法语：Classifieur linéaire
• 线性分类器的韩语：선형 분류
• 线性分类器的俄语：Линейный классификатор
• 线性分类器的印尼文：pengklasifikasi linear;