4. The method of claim 1 , further comprising: generating, by each computing device of the plurality of computing device using local training instances assigned to the computing device, a feature-to-instance index that maps each value of a feature to one or more training instances having the value for the feature; receiving, by a first computing device of the plurality of computing devices, a request to compute local statistics for the candidate condition; obtaining, by the first computing device, training instances matching the candidate condition by using one or more features of the candidate condition as input to the feature-to-instance index; computing local statistics for the candidate condition using matching training instances obtained using the feature-to-instance index; and providing, by the first computing device, the computed local statistics in response to the request to compute local statistics for the candidate condition.
4. The method of claim 1 , further comprising: generating, by each computing device of the plurality of computing device using local training instances assigned to the computing device, a feature-to-instance index that maps each value of a feature to one or more training instances having the value for the feature; receiving, by a first computing device of the plurality of computing devices, a request to compute local statistics for the candidate condition; obtaining, by the first computing device, training instances matching the candidate condition by using one or more features of the candidate condition as input to the feature-to-instance index; computing local statistics for the candidate condition using matching training instances obtained using the feature-to-instance index; and providing, by the first computing device, the computed local statistics in response to the request to compute local statistics for the candidate condition. 7. The method of claim 4 , wherein each training instance includes data representing a previously computed score for the selected first document.