Removes features whose weight is lower than the weight of the reference feature * threshold
Closes the evaluation file; evaluation is complete
Saves important info to this file for debug purposes
Displays the learned model in a human-readable format, for debug purposes
Displays the learned model in a human-readable format, for debug purposes
Will contain the test datums in svm_rank format, for offline testing
Opens the evaluation file, which contains datums in svm_rank format, for offline testing
Returns probabilities that can be used for ranking for a group of datums, from the same query These probabilities are obtained here from scoresOf() using softmax
Returns probabilities that can be used for ranking for a group of datums, from the same query These probabilities are obtained here from scoresOf() using softmax
All datums for one query
Keeps track of qids for the dump to evalFile
Saves the current model to a file
Saves the current model to a file
Returns scores that can be used for ranking for a group of datums, from the same query These scores do NOT have to be normalized, they are NOT probabilities!
Returns scores that can be used for ranking for a group of datums, from the same query These scores do NOT have to be normalized, they are NOT probabilities!
All datums for one query
Increments the qid; for the offline evaluation
Wrapper for SVMrank: trains using svm_rank_learn but predicts using native Scala code Only the linear kernel is supported User: mihais Date: 4/23/13 Last Modified: Fix compiler issue: import scala.io.Source.