標題: Titlebook: Optimization Based Data Mining: Theory and Applications; Yong Shi,Yingjie Tian,Jianping Li Book 2011 Springer-Verlag London Limited 2011 C [打印本頁] 作者: microbe 時間: 2025-3-21 16:10
書目名稱Optimization Based Data Mining: Theory and Applications影響因子(影響力)
書目名稱Optimization Based Data Mining: Theory and Applications影響因子(影響力)學科排名
書目名稱Optimization Based Data Mining: Theory and Applications網絡公開度
書目名稱Optimization Based Data Mining: Theory and Applications網絡公開度學科排名
書目名稱Optimization Based Data Mining: Theory and Applications被引頻次
書目名稱Optimization Based Data Mining: Theory and Applications被引頻次學科排名
書目名稱Optimization Based Data Mining: Theory and Applications年度引用
書目名稱Optimization Based Data Mining: Theory and Applications年度引用學科排名
書目名稱Optimization Based Data Mining: Theory and Applications讀者反饋
書目名稱Optimization Based Data Mining: Theory and Applications讀者反饋學科排名
作者: 定點 時間: 2025-3-21 22:25 作者: 靈敏 時間: 2025-3-22 03:35
1610-3947 re the two main components of data mining.Constructs SVM‘s f.Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Prog作者: Institution 時間: 2025-3-22 05:40 作者: 殘忍 時間: 2025-3-22 11:21
Robust Support Vector Machinese is involved. Then, we also establish a multi-class algorithm based on the above robust SVORM for general multi-class classification problem with perturbations. Furthermore, we construct a robust unsupervised and semi-supervised SVC for the problems with uncertainty information.作者: heterodox 時間: 2025-3-22 14:52
Multiple Criteria Linear Programmingrogramming. Then MCLP models for multiple classes and unbalanced training set are constructed separately. Furthermore, in order to ensure the existence of solution, we add regularization terms in the objective function of MCLP, and constructed regularized MCLP (RMCLP) model.作者: 你敢命令 時間: 2025-3-22 18:56
Non-additive MCLPure attributes with respect to the non-additive measure. The non-additive MCLP classification models are constructed in this chapter, and because the using of non-additive measure increases the computational cost, two major solutions to reduce the number of non-additive measures are given: hierarchical Choquet integral and the K-additive measure.作者: CRACK 時間: 2025-3-22 23:17
Firm Financial Analysisnt different problems in finance and banking. For comparison purpose, the result of MCQP is compared with four well-know classification methods: SPSS, linear discriminant analysis (LDA), Decision Tree based See5, SVMlight, and LibSVM.作者: 保存 時間: 2025-3-23 02:30
Personal Credit Managementhe MCQP classification, then compare the performance of MCQP with MCLP, linear discriminant analysis (LDA), decision tree (DT), support vector machine (SVM), and neural network (NN) methods in terms of predictive accuracy.作者: osculate 時間: 2025-3-23 06:24
Support Vector Machines for Classification Problemsandard algorithm .-support vector classification (.-SVC). Especially, considering the classification problem of which the training set with nominal attributes, we built a new SVM which can learn the distance of the nominal attribute values, to improve most popular approaches assuming that all attribute values are of equal distance from each other.作者: certitude 時間: 2025-3-23 12:11
Network Intrusion Detectionis collected by the STEAL lab at University of Nebraska at Omaha, The second dataset is the KDDCUP-99 data set which was provided by DARPA in 1998 for the evaluation of intrusion detection approaches.作者: 協(xié)迫 時間: 2025-3-23 16:43
Book 2011) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has作者: LARK 時間: 2025-3-23 18:17
MC2LP it for multi-class classification problem. We also formulated the Minimal Error and Maximal Between-class Variance (MEMBV) model by using the objective function of Fisher’s LDA (maximizing the between-class variance) and the MC2LP model for relaxing the constraints.作者: 邊緣 時間: 2025-3-24 00:50 作者: Hot-Flash 時間: 2025-3-24 02:39 作者: 懶洋洋 時間: 2025-3-24 09:33 作者: 異常 時間: 2025-3-24 14:11 作者: ARBOR 時間: 2025-3-24 17:17 作者: SAGE 時間: 2025-3-24 21:51 作者: 供過于求 時間: 2025-3-25 00:44 作者: 兵團 時間: 2025-3-25 07:09
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Lit sub-discipline.Provides observations and examples relevantDuring the latter part of 2004, Helen Buitenkamp of Springer Publishing emailed me that the first edition of Handbook of Urban and Community Forestry in the Northeast is the best volume in its field and inquired whether we’d be interested i作者: 美學 時間: 2025-3-25 09:14
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Liin the Northeast is the best volume in its field and inquired whether we’d be interested in compiling a second edition; I replied that we certainly would, and started working on it imme- ately. We have revised 14 out of 26 chapters in the first edition, and added two new authors. Many things in urba作者: 一夫一妻制 時間: 2025-3-25 15:13 作者: larder 時間: 2025-3-25 17:37 作者: CLAM 時間: 2025-3-25 23:35 作者: 行為 時間: 2025-3-26 02:38
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Liin the Northeast is the best volume in its field and inquired whether we’d be interested in compiling a second edition; I replied that we certainly would, and started working on it imme- ately. We have revised 14 out of 26 chapters in the first edition, and added two new authors. Many things in urba作者: Organization 時間: 2025-3-26 05:58
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Liin the Northeast is the best volume in its field and inquired whether we’d be interested in compiling a second edition; I replied that we certainly would, and started working on it imme- ately. We have revised 14 out of 26 chapters in the first edition, and added two new authors. Many things in urba作者: commune 時間: 2025-3-26 08:37 作者: Salivary-Gland 時間: 2025-3-26 12:51
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Liin the Northeast is the best volume in its field and inquired whether we’d be interested in compiling a second edition; I replied that we certainly would, and started working on it imme- ately. We have revised 14 out of 26 chapters in the first edition, and added two new authors. Many things in urba作者: phase-2-enzyme 時間: 2025-3-26 20:37 作者: 五行打油詩 時間: 2025-3-26 22:31
LOO Bounds for Support Vector Machinesto estimate the generalization error and then search for parameters so that this estimator is minimized. This requires that the estimators are both effective and computationally efficient. Leave-one-out (LOO) method is the extreme case of cross-validation, and in this case, a single point is exclude作者: 憲法沒有 時間: 2025-3-27 04:54 作者: Allure 時間: 2025-3-27 05:55
Unsupervised and Semi-supervised Support Vector Machinesers within each cluster are more closely related to one another than objects assigned to different clusters. Clustering algorithms provide automated tools to help identify a structure from an unlabeled set, and there is a rich resource of prior works on this subject. Efficient convex optimization te作者: 撫慰 時間: 2025-3-27 09:53 作者: 提升 時間: 2025-3-27 15:01
Feature Selection via ,,-Norm Support Vector Machinesset of features which contribute most to classification is also an important task in classification. The benefit of feature selection is twofold. It leads to parsimonious models that are often preferred in many scientific problems, and it is also crucial for achieving good classification accuracy in作者: Intractable 時間: 2025-3-27 19:34
Multiple Criteria Linear Programmingite objectives. The first objective separates the observations by minimizing the sum of the deviations (MSD) among the observations. The second maximizes the minimum distances (MMD) of observations from the critical value. According to the concept of Pareto optimality, we can seek the best tradeoff 作者: CAB 時間: 2025-3-27 22:46
MCLP Extensionslinear classification problems, and knowledge based MCLP for classification problems with prior knowledge. And on account of the limitation which the MCLP model failed to make sure and remove the redundancy in variables or attributes set, we constructed a new method combining rough set and the MCLP 作者: BLAZE 時間: 2025-3-28 05:24
Multiple Criteria Quadratic Programmingand to obtain some new models based on this general framework and to test the efficiency of these models by using some real problems. So we adopt some existed algorithms to solve these models. To propose some new and efficient methods for these models based on the structure of these models need to b作者: Interregnum 時間: 2025-3-28 08:00 作者: 彩色的蠟筆 時間: 2025-3-28 13:22
MC2LPiteria space that contains the tradeoffs of multiple criteria in MSD, this chapter constructed MC2LP model of which the structure has a constraint-level space that shows all possible tradeoffs of resource availability levels (i.e. the tradeoff of upper boundary and lower boundary), and also extended作者: Evocative 時間: 2025-3-28 17:39 作者: 豐富 時間: 2025-3-28 19:46
Personal Credit Managementcoring models can be classified into two categories: the first category concerns about application scores and the second category concerns behavior scores. Specifically, behavior scores are used to determine “raising or lowering the credit limit; how the account should be treated with regard to prom作者: 欲望小妹 時間: 2025-3-28 23:34 作者: Interdict 時間: 2025-3-29 03:09
Network Intrusion Detectionof network attacks is a pressing issue of today’s network security. Classification methods are one the major tools in network intrusion detection. A?successful network intrusion detection system needs to have high classification accuracies and low false alarm rates. In this chapter, we apply the ker作者: 情感脆弱 時間: 2025-3-29 07:50
Internet Service Analysisdred million RMB by 2005. This huge market dramatically enforced market competition among all E-mail service companies. The analysis for the pattern of lost customer accounts in hereby a significant research topic. This chapter focuses on this research to perform decision-making in reducing the cust作者: 猜忌 時間: 2025-3-29 12:14
Advanced Information and Knowledge Processinghttp://image.papertrans.cn/o/image/703139.jpg作者: profligate 時間: 2025-3-29 18:25 作者: 比目魚 時間: 2025-3-29 23:35 作者: 血友病 時間: 2025-3-29 23:59 作者: ELATE 時間: 2025-3-30 06:25 作者: 進取心 時間: 2025-3-30 11:35 作者: 培養(yǎng) 時間: 2025-3-30 12:38 作者: Migratory 時間: 2025-3-30 16:59
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Litrees in Chapter 17. All told, we have revised or replaced 16 chapters of the original 26; we’ve kept 10 chapters as originally written, and substituted two entirely new chapters, 1 and 14, respectively. With the emergence of urban and community forestry as the fastest growing part of our profession作者: 增減字母法 時間: 2025-3-30 23:13
trees in Chapter 17. All told, we have revised or replaced 16 chapters of the original 26; we’ve kept 10 chapters as originally written, and substituted two entirely new chapters, 1 and 14, respectively. With the emergence of urban and community forestry as the fastest growing part of our profession作者: 粗糙 時間: 2025-3-31 02:14 作者: 變白 時間: 2025-3-31 07:39
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Litrees in Chapter 17. All told, we have revised or replaced 16 chapters of the original 26; we’ve kept 10 chapters as originally written, and substituted two entirely new chapters, 1 and 14, respectively. With the emergence of urban and community forestry as the fastest growing part of our profession作者: 情愛 時間: 2025-3-31 13:15 作者: abstemious 時間: 2025-3-31 15:48
Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Litrees in Chapter 17. All told, we have revised or replaced 16 chapters of the original 26; we’ve kept 10 chapters as originally written, and substituted two entirely new chapters, 1 and 14, respectively. With the emergence of urban and community forestry as the fastest growing part of our profession作者: opprobrious 時間: 2025-3-31 21:35
LOO Bounds for Support Vector Machinesnsuming, thus methods are sought to speed up the process. An effective approach is to approximate the LOO error by its upper bound that is a function of the parameters. Then, we search for parameter so that this upper bound is minimized. This approach has successfully been developed for both support作者: 挑剔小責 時間: 2025-4-1 00:18
Unsupervised and Semi-supervised Support Vector Machinesicult computational problem in optimization and obtain high approximate solutions. In this chapter, we proposed several support vector machine algorithms for unsupervised and semi-supervised problems based on SDP.作者: outskirts 時間: 2025-4-1 04:12
Feature Selection via ,,-Norm Support Vector Machines selection in the SVM, in some of which they applied the ..-norm, ..-norm SVM and got competitive performance. We proposed two models in this chapter, ..-norm .-support vector classification (..-SVC) and ..-norm proximal support vector machine (..-PSVM), which separately combines .-SVC and PSVM with
