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ICIP
2009
IEEE
8 years 4 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
SGAI
2010
Springer
8 years 4 months ago
Induction of Modular Classification Rules: Using Jmax-pruning
The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree s...
Frederic T. Stahl, Max Bramer
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
8 years 4 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
CORR
2002
Springer
84views Education» more  CORR 2002»
8 years 6 months ago
Evaluating the Effectiveness of Ensembles of Decision Trees in Disambiguating Senseval Lexical Samples
This paper presents an evaluation of an ensemble
Ted Pedersen
ML
2008
ACM
135views Machine Learning» more  ML 2008»
8 years 6 months ago
Compiling pattern matching to good decision trees
We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Luc Maranget
JIKM
2008
98views more  JIKM 2008»
8 years 6 months ago
Knowledge-Based Expert System Development and Validation with Petri Nets
Expert systems (ESs) are complex information systems that are expensive to build and difficult to validate. Numerous knowledge representation strategies such as rules, semantic net...
Madjid Tavana
COMSIS
2006
156views more  COMSIS 2006»
8 years 6 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
IJCAI
1993
8 years 7 months ago
Rule-Based Regression
While decision trees have been used primarily for classification, they can also model regression or function approximation. Like classification trees, regression trees often yield...
Sholom M. Weiss, Nitin Indurkhya
ISMB
1996
8 years 7 months ago
Finding Genes in DNA Using Decision Trees and Dynamic Programming
This study demonstratesthe use of decision tree classifiers as the basis for a general gene-finding system. The system uses a dynamic programmingalgorithm that. finds the optimal ...
Steven Salzberg, Xin Chen, John Henderson, Kenneth...
ACL
1997
8 years 7 months ago
Learning Features that Predict Cue Usage
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanatio...
Barbara Di Eugenio, Johanna D. Moore, Massimo Paol...
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