Recent years have seen an increasing cross-fertilization between the fields of decision analysis and forecasting. Decision-analytic models often require forecasts as inputs, and aspects of the Bayesian decision-theoretic framework underlying decision analysis have proved useful to forecasting, parti
โฆ LIBER โฆ
On decision trees for orthants
โ Scribed by V.A. Vassiliev
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 332 KB
- Volume
- 62
- Category
- Article
- ISSN
- 0020-0190
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โฆ Synopsis
M. Rabin's principle asserts that the depth of any algebraic decision tree, recognizing a closed orthant in JR", is no less than n. Using the techniques of Newton polyhedra, we give the shortest possible proof of this fact, extending it to arbitrary collections of open or closed orthants, and apply it to trees distinguishing real polynomials having at least 1 real roots. @ 1997 Elsevier Science B.V.
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