In fact, a classifier is a more general concept, which includes data types and interfaces.
事实上，分类器是一个更为一般的概念，它包括数据类型和接口。
The first type of rule you normally create is a classifier which will group users into classifications.
通常创建的第一种类型的规则是把用户分组成分类的分类器。
Since most neighborhood association can be used as a classifier, and can store any simulated vector mode.
可用作自联想最邻分类器，并可存储任何模拟向量模式。
WNN can be seen as a classifier to distinguish the corrupted or uncorrupted pixels from others in both approaches.
在两种方案中，WNN都可以看作是一个区分污染与未污染像素的分类器。
When a new data fed into the integrated model, a classifier will deliver the new data into different non-linear local ANN model.
当新的信息进入该模型时，首先用分类器判别其类别，以确定用混合模型中的何种局部模型加以模拟。
The subclassification of noun takes a classifier as a form sign and can have different classifications with different layer levels.
名词的次分类以量词作为形式标志，可以分出层级不同的类别。
Then, combining IMD-Isomap and generalized regression neural network, which has a good ability for approximation, a classifier is proposed.
然后，结合泛化回归神经网络，设计出一种分类器。
A classifier shows that while each of these steps is manual, the business analyst believes they are all potential areas for workflow to be applied.
分类器显示尽管每个步骤都是手工执行的，业务分析人员相信它们都是可以应用工作流的潜在区域。
These features are used to train a B-P neural network, it is a classifier and can improve greatly the recognition rate of Chinese characters.
使用该B-P神经网络作为汉字的分类器，可以大大提高车牌汉字的识别率。
Finallly taking advantage of the trained network model as a classifier, we implemented a multi-level strategy Chinese character recognition system.
并利用训练后得到的网络作为分类器设计并实现了一种多级策略的汉字识别系统。
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data.
在统计建模中，有很多分类器构建算法，每个算法构造一组不同的关于数据的假设集合。
From the perspective of bit plane correlation, this algorithm extracts features, USES support vector machine as a classifier to detect LSB matching.
算法从位平面相关性的角度出发提取特征值，使用支持向量机作为分类器，对LSB匹配算法进行隐写分析。
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data.
为了获得最好的模型性能，挑选做出最合适假设的建模算法—而不只是选择你最熟悉那个算法，是很重要的。
In order to evaluate the classification efficiency of a classifier, this paper introduces the concepts of classification cut size and collection cut size.
为了评价分级机的分级效果，本文引入了分级粒径和收集粒径的概念。
Generally, you can think of a classifier as a class, but technically a classifier is a more general term that refers to the other three types above as well.
通常地，你可以把分类器当做类，但在技术上，分类器是更为普遍的术语，它还是引用上面的其它三种类型为好。
Constructed based on such an assumption, the BPNN might lead to pay heavy prices when used as a classifier even if the misclassifications took place rarely.
但基于这种假设构造的BPNN在进行分类时，即使是很少的失误也可能付出惨重的代价。
Eventually, the compatibility between the generated rules and patterns was used to construct a set of feature vectors, which were used to generate a classifier.
最后，通过计算规则和模式之间的兼容性指标来构造特征向量，构建支持向量机的分类器模型。
This paper, based on the theory and method of artificial nerve networks and fuzzy sets, puts forward a classifier model used for diagnosing the quasi-heath state.
利用人工神经网络与模糊集的理论和方法提出了诊断亚健康状态的一种分类器模型。
Adopts a classifier support vector machine which is a very good training algorithm, which can acquire very good generalization when the training datum are very few.
文中采用的分类器——支持向量机是一种能在训练样本数很少的情况下达到很好分类推广能力的学习算法。
Classification based on association (CBA) algorithm built a classifier based on the association rules, without considering the uncertainty in the classification problem.
关联规则分类器(CBA)利用关联规则来构造分类算法，但其没有考虑分类问题中的不确定性。
A pattern recognition problem is not only specified by a representation, but also by the set of examples given for training and evaluating a classifier in various stages.
模式识别问题不仅与表示方法有关，也跟用于在分类器设计各个阶段进行训练和测试的用例集有关。
Classification rules discovery is a procedure to construct a classifier through studying the training dataset. It is a very important part of data Mining and Knowledge discovery.
分类规则发现则是通过对训练样本数据集的学习构造分类规则的过程，是数据挖掘、知识发现的一个重要方面。
The manual neural network has become more and more important as a classifier. Learning from the environment adaptively and generalizing were the most advantages of neural network.
人工神经网络日渐成为一种重要的分类工具，其最大益处就在于它善于对环境的自适应学习，并且具有并行处理泛化能力。
Any class in the underlying ontology can be used as a classifier; the same classifier can be used to classify multiple entities and an entity can be associated with multiple classifiers.
基础本体中的任何类都可以用作分类器；可以使用同一分类器来对多个实体进行分类，并且一个实体可以与多个分类器关联。
Instead, we look to the composite structure notions of the UML 2.0 specification, which provides the ability to denote the internal organization of a classifier using "parts" and "connectors."
取而代之，我们指望uml 2.0规范的复合结构概念，其提供了表示使用“部件”和“连接器”的分类器的内部结构功能。
Attributes of each candidate enterprise could be regarded as a classifier, and the partner selection could be transformed into a classification issue with incomplete and uncertain information.
通过将备选企业的属性看作分类器，将伙伴选择问题转化为不完全、不确定性信息下的分类识别问题。
First selects texture features based on the gray level co-occurrence Matrix and then EBP-OP neural network is used as a classifier. The experimental results show that this method is very effective.
首先运用灰度共生矩阵提取图像的纹理特征，然后用EBP - OP算法对提取的纹理特征进行分类，并在此基础上实现一组纹理图像的检索，实验证明这种方法是有效的。
A typical model that started as just requirements may also include structural classifier models that express interactions.
一个从需求开始的典型模型可能还会包括结构化的表达交流的分类模型。
A typical model that started as just requirements may also include structural classifier models that express interactions.
一个从需求开始的典型模型可能还会包括结构化的表达交流的分类模型。
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