A Heuristic Program that Constructs Decision Trees
dc.date.accessioned | 2004-10-04T14:44:14Z | |
dc.date.accessioned | 2018-11-24T10:12:15Z | |
dc.date.available | 2004-10-04T14:44:14Z | |
dc.date.available | 2018-11-24T10:12:15Z | |
dc.date.issued | 1969-03-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/6175 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/6175 | |
dc.description.abstract | Suppose there is a set of objects, {A, B,...E} and a set of tests, {T1, T2,...TN). When a test is applied to an object, the result is wither T or F. Assume the test may vary in cost and the object may vary in probability or occurrence. One then hopes that an unknown object may be identified by applying a sequence if tests. The appropriate test at any point in the sequence in general should depend on the results of previous tests. The problem is to construct a good test scheme using the test cost, the probabilities of occurrence, and a table of test outcomes. | en_US |
dc.format.extent | 15630995 bytes | |
dc.format.extent | 1075245 bytes | |
dc.language.iso | en_US | |
dc.title | A Heuristic Program that Constructs Decision Trees | en_US |
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