A Heuristic Program that Constructs Decision Trees
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 apply...
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| Language: | en_US |
| Published: |
2004
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| Online Access: | http://hdl.handle.net/1721.1/6175 |
| Summary: | 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. |
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