分类(也即分类树或决策树)是一种数据挖掘算法，为如何确定一个新的数据实例的输出创建逐步指导。
Classification (also known as classification trees or decision trees) is a data mining algorithm that creates a step-by-step guide for how to determine the output of a new data instance.
在使用ClassificationWorkbench之前，要收集预先分类的样本数据(例如文档)，这些数据应该反映将用ICM进行分类的数据的典型情况。
Prior to using Classification Workbench, you'll collect pre-categorized sample data (for example, documents) representative of the data you expect to classify using ICM.
为了解决该方法存在的训练数据集问题，本文改进了现有的贝叶斯分类算法，提出了利用未标记数据提高贝叶斯分类器性能的方法。
In order to solve the problem existing in training data sets, present Bayes algorithm is im - proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.
本文对成像光谱仪数据信息提取和分类方法进行了探讨，提出了一个系统地对高分辨率成像光谱数据进行处理、分析、分类的方案。
This paper probes into data information extraction and classification methods for imaging spectrometer, puts a scheme to process and classify the information of imaging spectrometer.
提出平行坐标数据可视化技术与分类算法集成到一起进行可视化数据分类的方法。
A method of visual data classifying is improved by integrating visual technology of parallel coordinates with data classification algorithms.
利用距离公式，分析了数据集之间的分类及识别问题，为计算机中的数据集分类、识别提供了又一有力的方法。
Analysis the problem of classification and recognition of data sets though distance formula. This idea provides a powerful method to classify and distinguish data sets in computer.
分类是数据挖掘的一项重要任务，如何发现可理解的、令人感兴趣的分类规则是数据挖掘面临的一个主要问题。
Classification is an important task in data mining field, how to discover the intelligible and interesting classification rules is one of the main problems facing data mining.
在UCI数据集和大脑胶质瘤数据集上的实验结果表明新算法提高了分类器在不均衡数据集上的分类性能和预报能力。
Experimental results on UCI data sets and dataset of brain glioma show that MIEE improves the classification performance and prediction ability on the imbalanced dataset.
实验结果表明，PSS算法及其并行化算法是一种高效的数据分类算法，尤其适用于解决海量数据库中的数据分类问题。
The test results show that the PSS algorithm as well as its parallel algorithms are high efficient when they are used in classification of massive database.
公开了一种新的元数据分类方法，以及一种根据用户提问文件、利用新的元数据分类，建立信息入口的方法。
There is disclosed a new meta data category and a method of building an information portal in accordance with a user profile utilising the new meta data category.
数据分类是数据挖掘中的一个重要课题，研究各种高效的分类算法是数据挖掘的重要问题之一。
Data classification is an important task of data mining, and developing high-powered classification algorithm is one of the key problems for data mining.
引入减法聚类算法对样本数据进行分类，用得到的分类数据对局部模型参数进行离线辨识。
By introducing the subtraction clustering algorithm, the sample data are classified and the local model parameters are identified off-line using the corresponding data set.
文章对我国目前出现的错误的CIP分类数据实例进行了详细的辨别分析，并提出了控制CIP分类数据错误的措施。
The article delicately analyzes many examples of the wrong classification data of CIP emerging currently in China, and brings up lots of measures that control the classification data mistakes of CIP.
为了解决在没有已知标签样本的情况下数据流组合分类决策问题，提出一种基于约束学习的数据流组合分类器的融合策略。
To resolve combining classifiers decisions among ensemble classification over data streams without labeled examples, a transductive constraint-based learning strategy was proposed.
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。
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.
分类问题的任务是对已有类别的数据集用分类器挖掘一组规则集来预测新样例数据的类别。
The task of classification problem is to mine a rule-set for forecasting the class of a new example by studying the data sets with class label.
该算法有效的提高了分类精确度，并且能够直接支持关系数据库，运行时间远远小于基于ILP技术的关系数据分类算法。
This algorithm improved accuracy rate, support relational databases directly. Its running time is much lower than ILP based relational classification methods.
大规模数据集的分类是数据挖掘中的一个重要课题，而分类预测技术在税收领域的应用有着很好的前景。
Classification of large database is an important data Ming problem, and the application of classification and prediction technologies on tax collection has a bright prospect.
在UCI标准数据集合上进行测试，与airs和其他传统分类器进行比较，目的是研究基于人工免疫网络原理的数据分类方法的性能。
It is tested on the UCI standard data sets and compared with AIRS and the other classical classifiers. The aim is to research the performance of classifier based on artificial immune network.
将该模型应用于社会网络数据分类任务中，可以充分捕捉数据间的依赖关系，从而有效提高数据分类的准确度。
Applying the model to social network datasets classification can fully capture the dependencies among them, thus effectively improve the accuracy of classification.
该方法通过几个分类器间协同学习，选出标记可信度比较高的无标记数据，再利用这些数据对已有的分类器作进一步的改进。
This method utilizing co-learning among several classifiers, selects the unlabeled samples which have high confidence, and then refines each classifier with these samples.
在分析现有的高速数据包分类技术的基础上给出了一种基于CAM的高速数据包分类的实现方法。
This paper proposes an implementation method of packet classification based on CAM to provide fast packet classification.
为提高数据流分类的精确性和适应性，提出了一种新的数据流分类方法。
To improve the accuracy and adaptability of the classification of data stream, this paper presented a new method of classification.
分类的目的是构造一个分类模型，该 模型能把数据库中的数据项映射到某一个给定类别。
Target of classification is to find out a classification model. The model can map a single record in database to a pre-assumed class.
分类的目的是学会一个分类函数或分类模型，该模型能把数据库中的数据项映射到给定类别中的某一个。
The destination of classification is to learn a classification function or classification model that can map a data item to a preassigned class.
分类的目的是构造一个分类模型，该模型能把数据库中的数据项映射到某一个给定类别。
The target of classification is to find out a classification model. The model can map a single record in database to a pre-assumed class.
在数据挖掘中，分类是一种重要的技术，它能对大量有关数据进行分析、学习，并建立相应问题领域中的分类模型。
Classification, which is able to analyze and learn mass of relative data, establish corresponding classification model in some fields, is an important technique for data mining.
在数据挖掘中，分类是一种重要的技术，它能对大量有关数据进行分析、学习，并建立相应问题领域中的分类模型。
Classification, which is able to analyze and learn mass of relative data, establish corresponding classification model in some fields, is an important technique for data mining.
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