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PRL
2002
213views more  PRL 2002»
11 years 6 months ago
Character preclassification based on genetic programming
This paper presents a learning system that uses genetic programming as a tool for automatically inferring the set of classification rules to be used during a preclassification sta...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
ISCI
2008
181views more  ISCI 2008»
11 years 6 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
BMCBI
2006
94views more  BMCBI 2006»
11 years 6 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
BMCBI
2006
129views more  BMCBI 2006»
11 years 6 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
ICAISC
2010
Springer
11 years 6 months ago
Pruning Classification Rules with Reference Vector Selection Methods
Attempts to extract logical rules from data often lead to large sets of classification rules that need to be pruned. Training two classifiers, the C4.5 decision tree and the Non-Ne...
Karol Grudzinski, Marek Grochowski, Wlodzislaw Duc...
IFIP12
2008
11 years 8 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
11 years 10 months ago
A new version of the ant-miner algorithm discovering unordered rule sets
The Ant-Miner algorithm, first proposed by Parpinelli and colleagues, applies an ant colony optimization heuristic to the classification task of data mining to discover an ordered...
James Smaldon, Alex Alves Freitas
AI
2006
Springer
11 years 10 months ago
Classification Based on Logical Concept Analysis
This paper studies the problem of classification by using a concept lattice as a search space of classification rules. The left hand side of a classification rule is composed by a ...
Yan Zhao, Yiyu Yao
ADC
2006
Springer
125views Database» more  ADC 2006»
11 years 10 months ago
A reconstruction-based algorithm for classification rules hiding
Data sharing between two organizations is common in many application areas e.g. business planing or marketing. Useful global patterns can be discovered from the integrated dataset...
Juggapong Natwichai, Xue Li, Maria E. Orlowska
KDD
1997
ACM
135views Data Mining» more  KDD 1997»
11 years 11 months ago
Brute-Force Mining of High-Confidence Classification Rules
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Roberto J. Bayardo Jr.
books