找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Metaheuristic Clustering; Swagatam Das,Ajith Abraham,Amit Konar Book 2009 Springer-Verlag Berlin Heidelberg 2009 algorithms.data mining.ev

[復制鏈接]
查看: 7495|回復: 35
樓主
發(fā)表于 2025-3-21 18:21:11 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Metaheuristic Clustering
編輯Swagatam Das,Ajith Abraham,Amit Konar
視頻videohttp://file.papertrans.cn/632/631347/631347.mp4
概述Latest research on metaheuristic clustering
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Metaheuristic Clustering;  Swagatam Das,Ajith Abraham,Amit Konar Book 2009 Springer-Verlag Berlin Heidelberg 2009 algorithms.data mining.ev
描述.Cluster analysis means the organization of an unlabeled collection of objects or patterns into separate groups based on their similarity. The task of computerized data clustering has been approached from diverse domains of knowledge like graph theory, multivariate analysis, neural networks, fuzzy set theory, and so on. Clustering is often described as an unsupervised learning method but most of the traditional algorithms require a prior specification of the number of clusters in the data for guiding the partitioning process, thus making it not completely unsupervised. Modern data mining tools that predict future trends and behaviors for allowing businesses to make proactive and knowledge-driven decisions, demand fast and fully automatic clustering of very large datasets with minimal or no user intervention. ..In this volume, we formulate clustering as an optimization problem, where the best partitioning of a given dataset is achieved by minimizing/maximizing one (single-objective clustering) or more (multi-objective clustering) objective functions. Using several real world applications, we illustrate the performance of several metaheuristics, particularly the Differential Evolutio
出版日期Book 2009
關(guān)鍵詞algorithms; data mining; evolution; heuristics; kernel; knowledge; learning; metaheuristic; modeling; neural
版次1
doihttps://doi.org/10.1007/978-3-540-93964-1
isbn_softcover978-3-642-10071-0
isbn_ebook978-3-540-93964-1Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

書目名稱Metaheuristic Clustering影響因子(影響力)




書目名稱Metaheuristic Clustering影響因子(影響力)學科排名




書目名稱Metaheuristic Clustering網(wǎng)絡公開度




書目名稱Metaheuristic Clustering網(wǎng)絡公開度學科排名




書目名稱Metaheuristic Clustering被引頻次




書目名稱Metaheuristic Clustering被引頻次學科排名




書目名稱Metaheuristic Clustering年度引用




書目名稱Metaheuristic Clustering年度引用學科排名




書目名稱Metaheuristic Clustering讀者反饋




書目名稱Metaheuristic Clustering讀者反饋學科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:48:03 | 只看該作者
Conclusions and Future Research,the possible evolution of the proposed methods for handling clusters of non-spherical and shell type shapes, co-clustering and the problem of integrating together a feature selection module and a clustering module under the framework of Differential Evolution (DE).
板凳
發(fā)表于 2025-3-22 02:55:28 | 只看該作者
地板
發(fā)表于 2025-3-22 07:18:15 | 只看該作者
,Metaheuristic Pattern Clustering – An Overview,computing in pattern clustering and outlines the most promising evolutionary clustering methods. The chapter ends with a discussion on the automatic clustering problem, which remains largely unsolved by most of the traditional clustering algorithms.
5#
發(fā)表于 2025-3-22 08:51:49 | 只看該作者
6#
發(fā)表于 2025-3-22 13:47:09 | 只看該作者
Automatic Hard Clustering Using Improved Differential Evolution Algorithm,nal clustering techniques and one popular hierarchical clustering algorithm. The partitional clustering algorithms are based on Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm. An interesting practical application of the proposed method to automatic segmentation of images is also illustrated.
7#
發(fā)表于 2025-3-22 19:10:04 | 只看該作者
8#
發(fā)表于 2025-3-23 01:03:28 | 只看該作者
9#
發(fā)表于 2025-3-23 03:44:14 | 只看該作者
10#
發(fā)表于 2025-3-23 09:08:39 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-20 19:59
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復 返回頂部 返回列表
湖南省| 岑溪市| 苍溪县| 化德县| 紫阳县| 锡林郭勒盟| 根河市| 商都县| 亚东县| 云龙县| 株洲县| 和平区| 西昌市| 逊克县| 大余县| 磐安县| 静海县| 大冶市| 柘荣县| 清原| 永德县| 上杭县| 吐鲁番市| 广平县| 绩溪县| 清原| 元朗区| 潢川县| 威远县| 泸州市| 桐梓县| 鹤峰县| 涪陵区| 禄丰县| 墨竹工卡县| 麻江县| 沈丘县| 白山市| 庆城县| 凤庆县| 原阳县|