microbe
发表于 2025-3-21 16:10:18
书目名称Optimization Based Data Mining: Theory and Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0703139<br><br> <br><br>书目名称Optimization Based Data Mining: Theory and Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0703139<br><br> <br><br>
定点
发表于 2025-3-21 22:25:41
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灵敏
发表于 2025-3-22 03:35:53
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
Institution
发表于 2025-3-22 05:40:39
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残忍
发表于 2025-3-22 11:21:18
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.
heterodox
发表于 2025-3-22 14:52:32
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.
你敢命令
发表于 2025-3-22 18:56:57
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.
CRACK
发表于 2025-3-22 23:17:11
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.
保存
发表于 2025-3-23 02:30:30
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.
osculate
发表于 2025-3-23 06:24:37
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.