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Description: A distributed PSOSVM hybrid system with feature selection and parameter optimization
-Abstract
This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the classification accuracy with a small and appropriate feature subset. This optimization mechanism combined the discrete PSO with the
continuous-valued PSO to simultaneously optimize the input feature subset selection and the SVM kernel parameter setting. The hybrid PSO–SVM
data mining system was implemented via a distributed architecture using the web service technology to reduce the computational time. In a
heterogeneous computing environment, the PSO optimization was performed on the application server and the SVM model was trained on the
client (agent) computer. The experimental results showed the proposed approach can correctly select the discriminating input features and also
achieve high classification accuracy.
# 2007 Elsevier B.V. All rights reserved.
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Size: 565248 |
Author: alice |
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Description: 《实用数据挖掘》
本书对面向应用的数据挖掘方法进行了清晰的阐述，包括经典的多元统计方法、贝叶斯多元统计方法、基于机器学习的数据挖掘方法和基于计算的数据挖掘方法等。介绍了数据挖掘领域中许多最新的研究成果，如关联规则、序列规则、图示马尔可夫模型、基于存储的推理、信用风险和Web挖掘等。并详细介绍了选自实际工业项目的6个应用实例，强调了数据挖掘方法的实用性。 本书主要面向计算机科学、信息管理、应用统计学和经济学等专业的高年级本科生和研究生。对实际从事海量数据分析和处理的技术人员也有很好的指导作用和参考价值。 -Application-oriented book on data mining methods were clearly described, including the classic multivariate statistical methods, Bayesian multivariate statistical methods, data mining based on machine learning methods and calculations based on data mining methods. The field of data mining are introduced many of the latest research results, such as association rules, sequence rules, icons, Markov model, based on the storage of reasoning, credit risk, and Web mining. And gave details of the actual industrial projects selected from the six examples, emphasizing the usefulness of data mining methods. Book is mainly for computer science, information management, applied statistics and economics, and other professional undergraduate and graduate students. Actually engaged in massive data for analysis and processing of the technical staff are also very good guidance and reference value.
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Size: 13325312 |
Author: showna |
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Description: crawler data web for getting content web from internet source
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Size: 169984 |
Author: trungnam |
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Description: 序列模式挖掘是数据挖掘的一个重要分支，在序列事务及；有关信息处理中有着广泛的应用，如顾客购物习惯、web访问模式、科学实验过程分析、自然灾害预测、疾病治疗、药物检验以及{ sizej pos；
DNA等。序列模式挖掘算法有AprioriAll、GsP、F’reeSpan、本文将设计与实现针对string数据类型的算法，来对序列模式挖掘有更深入的剖析。-Sequence pattern mining is an important branch of data mining, and in the sequence matters the information processing has a wide range of applications, such as customer shopping habits, web access mode, the process of scientific experiments, natural disaster prediction, disease treatment, drug testing, and { sizej pos DNA and so on. Sequential pattern mining algorithm AprioriAll, GsP, F' reeSpan, this paper design and implementation of algorithms for string data types, to sequence pattern mining on a more in-depth analysis.
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Size: 288768 |
Author: 谢亚妮 |
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Description: A Novel Lexicalized HMM-based Learning Framework for Web Opinion Mining
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Size: 274432 |
Author: 王文学 |
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Description: Algorytm_A_priori, Web Mining Approaches
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Size: 64512 |
Author: misiek |
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Description: A Improved Hyperlink Induced Topics Search Algorithm Based on
Clonal Genetic Strategy for Web Mining
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Size: 92160 |
Author: shadow |
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Description: 数据挖掘 《机器学习与数据挖掘：方法与应用》，朱明等译，电子工业出版社-data mining conclude Classification,Estimation,Prediction,Affinity grouping or association rules,Clustering,Description and Visualization,Text, Web ,et al
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Size: 20729856 |
Author: 李杰 |
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Description: 机器学习与数据挖掘：方法和应用,本书分为5个部分,共18章,较为全面地介绍了机器学习的基本概念,并讨论了数据挖掘和知识发现中的有关问题及多策略学习方法,具体地阐述了机器学习与数据挖掘在工程设计,文本、图像和音乐,网页分析、计算机病毒和计算机控制,医疗诊断、生物医疗信号分析和水质分析中的生物信号处理等方面的应用情况。-Machine learning and data mining: methods and applications, the book is divided into five parts, 18 chapters, a more comprehensive introduction to the basic concepts of machine learning, and discuss the data mining and knowledge discovery and related issues in the multi-strategy learning methods and specifically describes the machine learning and data mining in engineering design, text, images and music, web analysis, computer viruses and computer control, medical diagnostics, biomedical signal analysis and water quality analysis and other aspects of biological signal processing applications.
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Size: 17956864 |
Author: 肖光润 |
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Description: Apriori algorithm Which is implemented for web mining concept.-Apriori algorithm Which is implemented for web mining concept.
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Size: 1712128 |
Author: Arun |
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Description: A data mining Alogorithm for Generalized Web Prefetching
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Size: 339968 |
Author: Le Thi Cam Tu |
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Description: Mining the E-commerce Data to Analyze the Target Customer Behavior is developed in Java. It clusters customer segments by using K-Means algorithm and data from web log of various e-commerce websites. Consequently, the results showed that there was a clear distinction between the segments in terms of customer behavior. It is seen that this data mining model can serve as an efficient vehicle for firms not only to predict the products or services that should be provided or improved for their target customer groups, but also to identify the right customers for a specific product family or service .
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Size: 416768 |
Author: Balaji |
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Description: 基于文件指纹的Web文本挖掘的原理论述，非常详细-Fingerprint-based Web text mining document the principles of discourse, very detailed
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Size: 57344 |
Author: 哈哈 |
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Description: Document containing Web Mining Techniques for
Recommendation and Personalization
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Size: 57344 |
Author: jijo |
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Description: WEB MINING web挖掘研究论文-WEB MINING web mining paper
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Size: 189440 |
Author: fantian |
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Description: Web数据挖掘原理及实现 web mining-Principle and Implementation of Web data mining web mining
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Size: 50176 |
Author: fantian |
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Description: Web数据挖掘研究 web mining-Web data mining web mining
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Size: 32768 |
Author: fantian |
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Description: Web数据挖掘的原理_方法及用途 web mining-Web data mining methods and uses the principle of _
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Size: 120832 |
Author: fantian |
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Description: web挖掘中的用具fcm均值聚类的算法,用于电子商务网站中对数据清洗过的结果进行分析的算法-web mining equipment in the fcm-means clustering algorithm, the data for e-commerce sites cleaned in the analysis of the results of the algorithm
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Size: 1315840 |
Author: 刘昊平 |
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Description: Mining.the.Social.Web.Matthew.A.Russell.文字版-Mining the Social Web Matthew A Russell
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Size: 5792768 |
Author: Elong |
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