分类的

One of the classification models that based on statistic theory is Bayesian network classifier.

目前已知的分类算法中一种重要的基于统计方法的模型是贝叶斯分类模型，在贝叶斯分类模型中实用性最高和应用最广泛的是朴素贝叶斯分类器。

Constructed by standard binary classes support vector machine, present multiclass SVMs are usually very slow to be trained. When a large number of categories of data are to be classified, the training work could be very difficult. By extending the hypersphere one-class SVM to a hypersphere multiclass SVM, we build a fast training classifier HSOC-SVM. Its training speed is higher than that of the present multiclass classifiers, because each category data trains only one HSOC-SVM.

目前的多类分类器大多是经二分类器组合而成的，存在训练速度较慢的问题，在分类类别多的时候，会遇到很大困难，超球体多类支持向量机将超球体单类支持向量机扩展到多类问题，由于每类样本只参与一个超球体支持向量机的训练，因此，这是一种直接多类分类器，训练效率明显提高。

In the classification part, we propose a Hybrid Classification Tree with learning capability to classify the recipe of a working wafer in the ion implanter, and a k-fold cross validation error is treated as the accuracy of the classification result.

在分类部分，我们提出具有学习能力的混合型分类树，针对离子植入机里正在运作晶圆的配方进行分类，所得到的k-交叠相互验证错误率则用来作为分类结果的准确性。

At first, four feature attributes were built by content of DNA's four bases. By increasing length attribute of DNA sequence in the space to extent the feature attribute space. Finally, the classification of hyperplane was obtained on the basis of available samples training by using SVC in the feature attribute space.

根据SVM分类器的要求建立特征属性空间，首先由每个DNA中4个碱基的含量得到4个特征属性，然后在此空间中扩充DNA序列长度的属性，最后根据SVM分类器对已知的DNA分类样本做训练得到分类超平面。

The taxonomic system is very different from the one used widespreadly by foreign scholars. The taxonomic status and the phylogentic relationships among the five families Catantopidae, Acrididae, Oedipodidae, Arcypteridae, Gomphoceridae is the main controversy. In order to provide enough proofs for improving the taxonomic system, it is necessary to study the phylogeny of five families of Acridoidea based on molecular markers.

但此分类系统与国外所用的分类系统差别较大，争论的焦点在于斑腿蝗科、剑角蝗科、斑翅蝗科、网翅蝗科和槌角蝗科5个科的分类地位及其相互关系，因此我们从分子水平上探讨这5科的系统发育关系，为完善蝗总科分类系统提供一些必要的证据。

In the paper, I analyze and deal with the primal data of eradiate noise to get the ratio of recognition and make a conclusion that the feature extraction arithmetic and classifier arithmetic are efficient.

本文利用两次松花湖湖泊试验所采哈尔滨工程大学硕士学位论文集的船舶辐射噪声数据进行分析处理，为了验证模糊融合分类器的分类性能，依据具体情况做了两个分类试验，给出各自具体的识别率，并由此得出了相应的结论，即本文所选取的特征提取和分类器算法基本上是有效的。

A new schema matching approach based on formal concept analysis is introduced. The procedure contains three steps. Firstly, the evidence about each element being matched is initialized by applying name classifier and description classifier which are built on Naive B ayes Text Classifier to classify the names and descriptions of the elements.

提出了一种基于形式概念分析的模式匹配的FCABSM方法，该方法由3部分组成：首先，以朴素贝叶斯文本分类算法为基础设计名称分类算法及描述分类算法，分类目标模式与待匹配模式的元素名以及元素描述，为模式间元素的匹配提供初始依据。

The recognition rates of single character of three classifiers are all higher than 97%.

分类器1、分类器2和分类器3对测试集的单字识别率都达到97％以上。

The traditional classification methods only use one single classifier, which may lead to onesidedness, low accuracy, and that the samples nearby the Support Vector Machine hyperplanes are more easily misclassified. To solve these problems, the multifeature fusion method based on SVM and KNearest Neighbor classifiers was presented in this paper.

针对传统分类方法只采用一种分类器而存在的片面性，分类精度不高，以及支持向量机分类超平面附近点易错分的问题，提出了基于支持向量机和k近邻的多特征融合方法。

The effects of influence factors on residents'action of waste sorting collection,including waste throwing frequency,waste sorting percentage,distance between waste collection site and dwelling houses,time of waste clearing away and so on in waste sorting collection system ,were investigated by questionnaire in both EI Paso and Asturias.

采用问卷方式对EIPaso和西班牙Asturias垃圾分类回收系统中投放垃圾频率、垃圾分类比率、垃圾收集点与居民住宅距离、垃圾清运时间等对居民分类回收行动的影响进行了调查。

Lugalbanda was a god and shepherd king of Uruk where he was worshipped for over a thousand years.

Lugalbanda 是神和被崇拜了一千年多 Uruk古埃及喜克索王朝国王。

I am coming just now,' and went on perfuming himself with Hunut, then he came and sat.

我来只是现在，'歼灭战perfuming自己与胡努特，那麼，他来到和SAT 。