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SGAI
2007
Springer
14 years 1 months ago
Towards a Computationally Efficient Approach to Modular Classification Rule Induction
Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision T...
Frederic T. Stahl, Max Bramer
IFIP12
2008
13 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
EDBT
2000
ACM
13 years 11 months ago
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
BMCBI
2005
112views more  BMCBI 2005»
13 years 7 months ago
Towards precise classification of cancers based on robust gene functional expression profiles
Background: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. Th...
Zheng Guo, Tianwen Zhang, Xia Li, Qi Wang, Jianzhe...
CIKM
2006
Springer
13 years 11 months ago
Multi-evidence, multi-criteria, lazy associative document classification
We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through...
Adriano Veloso, Wagner Meira Jr., Marco Cristo, Ma...