这些类别帮助确定对指定的数据使用哪种数据隐私屏蔽算法。
These categories help determine which of the data privacy masking algorithms to use for the specified data.
GRDDL还允许使用配置文件文档，而这些文档又为特定类别的网页和数据词汇引用适当的转换算法。
GRDDL also allows the use of profile documents, which in turn reference the appropriate transformation algorithms for a particular class of Web pages and data vocabularies.
这是什么呢？这种算法属于什么类别呢？，有人知道吗？大点声？
What is this? What category of algorithm is that? Somebody? Louder?
学习算法分为几个不同的类别。
The types of learning algorithms fall along several classifications.
说明如何对应演算法名称至密码编译类别。
Describes how to map algorithm name to a cryptography class.
提出了一种基于密度的孤立点因子算法和一种基于粗集理论的属性类别差异数据归约算法。
The Out-lier algorithm based on density and attribution classical discrepant data protocol algorithm based on rough set theory were presented.
提出了一种基于类别特征矩阵的决策树算法。
An algorithm of the decision tree based on class feature matrix is proposed.
充分考虑了可辨识矩阵的特性，提出一种基于类别特征矩阵的决策规则提取算法。
An extracting rules algorithm based on class feature matrix is presented, which has made use of the characteristic of discernibility matrix.
算法采用有向图来表示攻击类别及其逻辑关系，按照前向匹配和缺项匹配的方式对报警进行关联。
In this algorithm, an extended directed graph is used to show attack types and their relations, while the correlation is performed according to the method of forwards matching and absent matching.
该方法基于半模糊核聚类算法挖掘不同类别之间的衔接和离散信息，设计树型支持向量机的树型结构，克服其差错积累问题。
The method mines information on overlap between classes, designs the tree structure and overcomes the misclassification of tree-structured SVMs based on the semi-fuzzy kernel clustering algorithm.
提出一种基于粗糙集理论的分类别进行规则抽取的算法。
An algorithm based on rough set theory for extracting rules from data class by class is proposed.
仍然有些算法很容易就可以被归入好几个类别，好比学习矢量量化，它既是受启发于神经网络的方法，又是基于实例的方法。
There are still algorithms that could just as easily fit into multiple categories like Learning Vector Quantization that is both a neural network inspired method and an instance-based method.
在特征向量的选择中，本算法还用到了训练集的类别标签和类别平均向量的判别信息。
In selecting vectors, the algorithm also USES the class label of training set and the judgment information of class mean vector.
提出了一种基于核的多类别模式识别算法(简称核子空间法，KSPM)，依据此算法建立了多故障分类器。
A novel multi-class classifier with kernels, namely kernel Subspace Methods (KSPM), was presented, and a multi-fault classifier based on the algorithm was constructed.
该文引入了属性值类别计数器的概念，然后重点介绍了ID4算法和ID5R算法，并在最后加以比较。
This text introduced the concept of the classification counter of attribute value, then introduced ID4 algorithm and ID5R algorithm especially, and compare at the end.
然后结合隶属度变量构建优化模型，利用具有动态惩罚函数的遗传算法求解，计算得到各方案的所属类别。
Then optimization model with the membership degree is constructed. It is solved by using genetic algorithms with dynamical castigatory function.
此分类算法首先计算未知类别样本的重构系数，定义一种误差作为判别标准，根据此误差的大小判断样本的类别归属。
This algorithm firstly computes the reconstruction weights of unknown samples. Then an error, on which the class of samples can be decided based, is defined as a criterion.
该算法依据训练文本集的特征词句子环境，获取识别文本主题类别的特征词集合。
Both of the algorithms based on the context of feature words in sentence of training texts can get a set of feature words that identify the category of a text.
使用K2结构学习算法选出具有类别可分性的波段，进一步利用互信息测试对遥感波段之间的相关性做分析，去除冗余信息。
Firstly to select the bands that have class separability by K2 algorithm, then remove the redundant bands based on conditional mutual information test.
本文算法使得所提特征之间相互无关，这样降低了数据冗余，同时考虑到类别信息，使得投影后的类间区分度加强了。
The algorithm proposed here not only imposes an uncorrelated constraint to reduce data redundancy, but also utilizes the class information and the interclass separability after projection is enhanced.
由于学校管理模式不同、课程类别不同，选课算法的公平规则也不同。
Because of the different modes of management and different course students take, the fairness of algorithm differs.
虽然不管是类别还是算法都不是全面详尽的，但我认为它们都具有代表性，有助于你对整个领域有一个大致的了解。
It is not exhaustive in either the groups or the algorithms, but I think it is representative and will be useful to you to get an idea of the lay of the land.
对于已知行为，采用加权支持向量机分类算法来识别其行为类别；
For the known activities, the weighted support vector machine (WSVM) is used to recognize their types.
目前国际上对类别不平衡数据的研究主要集中在两个个层面：对数据集的处理和对分类算法的改进。
At present, researches on class imbalance problems mainly focus on two aspects: dataset processing and classification method improving.
这种算法主要体现了两大原则，一是基于待分类别的光谱特征优化与参量化原则，二是类别判定中的模糊定义与专家决策原则。
It is designed out in accord with two principles: one is the spectral feature optimization and parameterization, another is fuzzy and expert decision in pixel identification.
同时，这些算法几乎都是在单层次上做一次终结式分类，没有考虑到文本类别的逐层分类。
Meanwhile, almost all of these algorithms are built on single hierarchical platform, without considering the hierarchies of text category.
采用最大似然准则的聚类算法其类别接受域为球形或椭球形，可以与模式的分布匹配更好。
Using maximum likelihood criterion in clustering algorithms, the clusters have spherical or ellipsoidal receptive fields and match the distributes of patterns better.
利用邻域保护性能和特征的类别判别能力之间的关系，使得该算法提取的特征具有更好的分类性能。
Compared with NPE algorithm, the orthogonal vectors have the better locality preserving power, thus the stronger discriminant power can be gotten and the error rate reduced.
利用邻域保护性能和特征的类别判别能力之间的关系，使得该算法提取的特征具有更好的分类性能。
Compared with NPE algorithm, the orthogonal vectors have the better locality preserving power, thus the stronger discriminant power can be gotten and the error rate reduced.
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