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KDD
2008
ACM
167views Data Mining» more  KDD 2008»
15 years 11 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
15 years 11 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
15 years 11 months ago
BLOSOM: a framework for mining arbitrary boolean expressions
We introduce a novel framework (BLOSOM) for mining (frequent) boolean expressions over binary-valued datasets. We organize the space of boolean expressions into four categories: p...
Lizhuang Zhao, Mohammed J. Zaki, Naren Ramakrishna...
KDD
2004
ACM
314views Data Mining» more  KDD 2004»
15 years 11 months ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
15 years 11 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...
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