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Titlebook: Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining; Hassan AbouEisha,Talha Amin,Mikhail Moshkov Book 2019 Sp

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發(fā)表于 2025-3-28 16:44:08 | 只看該作者
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發(fā)表于 2025-3-29 01:57:58 | 只看該作者
Book 2019ation of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. Th
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發(fā)表于 2025-3-29 03:17:57 | 只看該作者
Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining
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發(fā)表于 2025-3-29 08:05:37 | 只看該作者
More Applications of Multi-stage Optimization of Decision Treese show results on the complexity of two problems: problem of eight element sorting and a modified majority problem. Finally, the chapter concludes with an algorithm for optimizing decision tests for decision tables.
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發(fā)表于 2025-3-29 15:27:45 | 只看該作者
Bi-criteria Optimization Problem for Decision Trees: Cost Versus Uncertaintyd uncertainty measure. We end this chapter with some illustrative examples and a discussion of multi-pruning of decision trees with applications from knowledge representation and classification. The classifiers constructed by multi-pruning process often have better accuracy than the classifiers constructed by CART.
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發(fā)表于 2025-3-29 18:48:59 | 只看該作者
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發(fā)表于 2025-3-30 07:50:01 | 只看該作者
Book 2019nd solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform
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