4 citations · 7 across the 13 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2016
Ensemble Validation: Selectivity has a Price, but Variety is Free
Eric Bax, Farshad Kooti
Suppose some classifiers are selected from a set of hypothesis classifiers to form an equally-weighted ensemble that selects a member classifier at random for each input example. T…
stat.ML2015★ 1 cited
Some Theory For Practical Classifier Validation
Eric Bax, Ya Le
We compare and contrast two approaches to validating a trained classifier while using all in-sample data for training. One is simultaneous validation over an organized set of hypot…
stat.ML2015
Improved Error Bounds Based on Worst Likely Assignments
Eric Bax
Error bounds based on worst likely assignments use permutation tests to validate classifiers. Worst likely assignments can produce effective bounds even for data sets with 100 or f…