Download A branch-and-bound algorithm for discrete multi-factor by Niu Shu-fen, Wang Guo-xin, Sun Xiao-ling PDF

By Niu Shu-fen, Wang Guo-xin, Sun Xiao-ling

During this paper, a brand new branch-and-bound set of rules in accordance with the Lagrangian twin rest and non-stop rest is proposed for discrete multi-factor portfolio choice version with roundlot restrict in monetary optimization. This discrete portfolio version is of integer quadratic programming difficulties. The separable constitution of the version is investigated by utilizing Lagrangian rest and twin seek. Computational effects exhibit that the set of rules is able to fixing real-world portfolio issues of information from US inventory industry and randomly generated try issues of as much as a hundred and twenty securities.

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However, this would not capture the nuances of hierarchical classification. ” The metric above would consider this classification as absolutely wrong, 2. ” With this in mind, we adapt the precision and recall metrics from information retrieval [CM63]. We first introduce an auxiliary definition. Given a set of categories N, we “expand” it by including all the subcategories of the categories in N — in essence, taking the downward closure of the set of categories N in the classification hierarchy C.

However, this approach would require a much larger number of query probes and would considerably increase the cost of our method. Previous work in hierarchical document classification [Sah98] has outlined other approaches to address this problem, but a full discussion of such extensions is beyond the scope of this work. We simply note here that the techniques used in the case of hierarchical document classification can be adapted for use in the case of hierarchical database classification that we address in this thesis.

To keep our experiments manageable, we did not try this otherwise interesting variation. We now turn to reporting the results of the experimental comparison of the different versions of QProber, Document Sampling, and Title-based Querying over the 400 unseen databases in the Controlled set and the databases in the Web set. 2, Definition 4, the ideal classification of a database depends on two parameters: τs (for specificity) and τc (for coverage). The values of these parameters are an “editorial decision,” as discussed previously.

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