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Cost of Different Algorithms for α = 1.

Cost of Different Algorithms for α = 1.

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Cost of Different Algorithms for α = 1.
Maximum and Average Number of Stars per Hypothesis and per Test in...
Optimal Decision Tree and Submodular Function Ranking Under Noisy Outcomes
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  • Jan 2022
A fundamental task in active learning involves performing a sequence of tests to identify an unknown hypothesis that is drawn from a known distribution. This problem, known as optimal decision tree induction, has been widely studied for decades and the asymptotically best-possible approximation algorithm has been devised for it. We study a generali...

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... Tables 1, Tables 2 and Tables 3 show the unknowns per test, we also have included these parameters as well as their average values in Table 4. Table 5 summarizes the results on WISER-ORG with clique and neighborhood stopping criteria. ...

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