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» Improving Mining Quality by Exploiting Data Dependency
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SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 7 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
14 years 2 months ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont
AAI
2007
132views more  AAI 2007»
13 years 7 months ago
Incremental Extraction of Association Rules in Applicative Domains
In recent years, the KDD process has been advocated to be an iterative and interactive process. It is seldom the case that a user is able to answer immediately with a single query...
Arianna Gallo, Roberto Esposito, Rosa Meo, Marco B...
NPC
2007
Springer
14 years 1 months ago
A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques
Parallelism is one of the main sources for performance improvement in modern computing environment, but the efficient exploitation of the available parallelism depends on a number ...
Shun Long, Grigori Fursin, Björn Franke
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 8 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang