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» Adjusting for Multiple Comparisons in Decision Tree Pruning
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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
ICDE
2009
IEEE
151views Database» more  ICDE 2009»
14 years 9 months ago
Decision Trees for Uncertain Data
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
13 years 8 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
WSC
2008
13 years 9 months ago
The improved sweep metaheuristic for simulation optimization and application to job shop scheduling
We present an improved sweep metaheuristic for discrete event simulation optimization. The sweep algorithm is a tree search similar to beam search. The basic idea is to run a limi...
George Jiri Mejtsky
SAC
2005
ACM
14 years 28 days ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...