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JMLR
2012
13 years 16 days ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
ML
2000
ACM
105views Machine Learning» more  ML 2000»
14 years 10 months ago
Multiple Comparisons in Induction Algorithms
Abstract. A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction ...
David D. Jensen, Paul R. Cohen
JMLR
2006
135views more  JMLR 2006»
14 years 10 months ago
Statistical Comparisons of Classifiers over Multiple Data Sets
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Janez Demsar
123
Voted
ICMLA
2010
14 years 8 months ago
Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel
Abstract--In this paper we propose a probabilistic classification algorithm with a novel Dynamic Time Warping (DTW) kernel to automatically recognize flight calls of different spec...
Theodoros Damoulas, Samuel Henry, Andrew Farnswort...
ICML
2010
IEEE
14 years 11 months ago
Learning Programs: A Hierarchical Bayesian Approach
We are interested in learning programs for multiple related tasks given only a few training examples per task. Since the program for a single task is underdetermined by its data, ...
Percy Liang, Michael I. Jordan, Dan Klein