@inproceedings{8aee8cc4a78c473198fcab740ad5c669,
title = "Combination of Conformal Predictors for Classification",
abstract = "The paper presents some possible approaches to the combination of Conformal Predictors in the binary classification case. A first class of methods is based on p-value combination techniques that have been proposed in the context of Statistical Hypothesis Testing; a second class is based on the calibration of p-values into Bayes factors. A few methods from these two classes are applied to a real-world case, namely the chemoinformatics problem of Compound Activity Prediction. Their performance is discussed, showing the different abilities to preserve of validity and improve efficiency. The experiments show that P-value combination, in particular Fisher{\textquoteright}s method, can be advantageous when ranking compounds by strength of evidence.",
author = "Paolo Toccaceli and Alexander Gammerman",
year = "2017",
month = jun,
day = "13",
language = "English",
volume = "60",
series = "The Proceedings of Machine Learning Research",
pages = "39--61",
editor = "Lawrence, {Neil } and Mark Reid",
booktitle = "Proceedings of Machine Learning Research",
}