Sciweavers

CEC
2010
IEEE
13 years 5 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
CEC
2010
IEEE
13 years 5 months ago
Improving GP classification performance by injection of decision trees
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
Rikard König, Ulf Johansson, Tuve Löfstr...
IJCAI
1989
13 years 5 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
AAAI
1990
13 years 5 months ago
What Should Be Minimized in a Decision Tree?
In this paper, we address the issue of evaluating decision trees generated from training examples by a learning algorithm. We give a set of performance measures and show how some ...
Usama M. Fayyad, Keki B. Irani
NIPS
1996
13 years 5 months ago
Hidden Markov Decision Trees
We study a time series model that can be viewed as a decision tree with Markov temporal structure. The model is intractable for exact calculations, thus we utilize variational app...
Michael I. Jordan, Zoubin Ghahramani, Lawrence K. ...
COLING
1996
13 years 5 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
NIPS
2004
13 years 5 months ago
Using Random Forests in the Structured Language Model
In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
Peng Xu, Frederick Jelinek
FLAIRS
2006
13 years 5 months ago
Generalized Entropy for Splitting on Numerical Attributes in Decision Trees
Decision Trees are well known for their training efficiency and their interpretable knowledge representation. They apply a greedy search and a divide-and-conquer approach to learn...
Mingyu Zhong, Michael Georgiopoulos, Georgios C. A...
FCS
2006
13 years 5 months ago
Principles of Optimal Probabilistic Decision Tree Construction
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
EMNLP
2006
13 years 5 months ago
Learning Information Status of Discourse Entities
In this paper we address the issue of automatically assigning information status to discourse entities. Using an annotated corpus of conversational English and exploiting morpho-s...
Malvina Nissim