Currently, we have no weights logic at all.
We pick the first X examples to run in case prediction size is bigger than the specified limit.
Sometimes it leads to predictions with critical tests ignored. We need to extract prediction "pruning" logic to separate class so we alter behaviour with different strategies.
Future expected strategies:
First tests
Random tests
Tests with weights
Expected outcome
A class that encapsulates current logic ('first tests') that can be easily substituted with a different class with different logic.
Currently, we have no weights logic at all. We pick the first X examples to run in case prediction size is bigger than the specified limit.
Sometimes it leads to predictions with critical tests ignored. We need to extract prediction "pruning" logic to separate class so we alter behaviour with different strategies.
Future expected strategies:
Expected outcome
A class that encapsulates current logic ('first tests') that can be easily substituted with a different class with different logic.