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Part of the expected utility comes from this point, the rest from the expected probabilities of the other budget-1 points
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It also adds another example notebook |
Implemented random and uncertainty as initial examples
Now baked in to IndividualScoringQueryStrat
Found I was having to implement a "many" and "single" version in order to achieve computational efficiency. This version is less clunky
Clearer that you want "targets" than "positives"
Also fixed some flake issues
Code crashes with a useless error message when there are fewer good points available than we need to fill a batch of selections
Fix bug in MCAL Regression
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From my understanding, the current implementation of active search is missing the probability of the choice point in the effective utility. This PR changes the scoring function for active search to use the probability of the point being the positive class, which recovers the behavior such that if the budget is
1then the active search is equivalent to greedy selection.