Showing papers on "Decision tree learning published in 1976"

The synthetic approach to decision table conversion

Abstract: Previous approaches to the problem of automatically converting decision tables to computer programs have been based on decomposition At any stage, one condition is selected for testing, and two smaller problems (decision tables with one less condition) are created An optimal program (with respect to average execution time or storage space, for example) is located only through implicit enumeration of all possible decision trees using a technique such as branch-and-bound The new approach described in this paper uses dynamic programming to synthesize an optimal decision tree from which a program can be created Using this approach, the efficiency of creating an optimal program is increased substantially, permitting generation of optimal programs for decision tables with as many as ten to twelve conditions