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BMCBI
2004
181views more  BMCBI 2004»
15 years 6 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
15 years 4 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
SIGMOD
2012
ACM
240views Database» more  SIGMOD 2012»
13 years 9 months ago
Finding related tables
We consider the problem of finding related tables in a large corpus of heterogenous tables. Detecting related tables provides users a powerful tool for enhancing their tables wit...
Anish Das Sarma, Lujun Fang, Nitin Gupta 0003, Alo...
IPMI
2003
Springer
16 years 7 months ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...
KDD
2009
ACM
202views Data Mining» more  KDD 2009»
16 years 7 months ago
Correlated itemset mining in ROC space: a constraint programming approach
Correlated or discriminative pattern mining is concerned with finding the highest scoring patterns w.r.t. a correlation measure (such as information gain). By reinterpreting corre...
Siegfried Nijssen, Tias Guns, Luc De Raedt