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ECML
2007
Springer
13 years 11 months ago
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Anneleen Van Assche, Hendrik Blockeel
AIPS
2011
12 years 11 months ago
Sample-Based Planning for Continuous Action Markov Decision Processes
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
ICML
2001
IEEE
14 years 8 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan
ICDM
2010
IEEE
154views Data Mining» more  ICDM 2010»
13 years 5 months ago
Discrimination Aware Decision Tree Learning
Abstract--Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute , find a classifier with high predictive accu...
Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
SIGKDD
2000
231views more  SIGKDD 2000»
13 years 7 months ago
KDD-99 Classifier Learning Contest: LLSoft's Results Overview
Kernel Miner is a new data-mining tool based on building the optimal decision forest. The tool won second place in the KDD'99 Classifier Learning Contest, August 1999. We des...
Itzhak Levin