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CEC
2010
IEEE
11 years 10 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
IJCAI
1989
11 years 11 months ago
Generating Better Decision Trees
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
Steven W. Norton
COLING
1996
11 years 11 months ago
Decision Tree Learning Algorithm with Structured Attributes: Application to Verbal Case Frame Acquisition
The Decision Tree Learning Algorithms (DTLAs) are getting keen attention from the natural language processing research comlnunity, and there have been a series of attempts to appl...
Hideki Tanaka
RA
2003
135views Robotics» more  RA 2003»
11 years 11 months ago
Behavioural Cloning and Robot Control
Behavioural cloning is a method by which a machine learns control skills through observing what a human controller would do in a certain set of circumstances. More specifically, t...
Claire D'Este, Mark O'Sullivan, Nicholas Hannah
ACL
2001
11 years 11 months ago
Automated Subcategorization of Named Entities
There has been much interest in the recent past concerning the possibilities for automated categorization of named entities. The research presented here describes a method for the...
Michael Fleischman
ECAI
2008
Springer
11 years 11 months ago
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo
DIS
2004
Springer
12 years 1 months ago
Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data
Abstract. Attribute value taxonomies (AVTs) have been used to perform AVT-guided decision tree learning on partially or totally missing data. In many cases, user-supplied AVTs are ...
Jinu Joo, Jun Zhang 0002, Jihoon Yang, Vasant Hona...
IDA
2005
Springer
12 years 3 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
ECML
2007
Springer
12 years 3 months ago
Decision Tree Instability and Active Learning
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
Kenneth Dwyer, Robert Holte
QSIC
2007
IEEE
12 years 4 months ago
Learning Effective Oracle Comparator Combinations for Web Applications
Web application testers need automated, effective approaches to validate the test results of complex, evolving web applications. In previous work, we developed a suite of automate...
Sara Sprenkle, Emily Hill, Lori L. Pollock
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