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» Using Anonymized Data for Classification
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140
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ECCV
2010
Springer
15 years 7 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
137
Voted
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
15 years 8 months ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
155
Voted
PAA
2002
15 years 2 months ago
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford
203
Voted
ICDE
2003
IEEE
146views Database» more  ICDE 2003»
16 years 4 months ago
Similarity Search in Sets and Categorical Data Using the Signature Tree
Data mining applications analyze large collections of set data and high dimensional categorical data. Search on these data types is not restricted to the classic problems of minin...
Nikos Mamoulis, David W. Cheung, Wang Lian
134
Voted
CATA
2004
15 years 4 months ago
Decision Tree Induction for Dynamic, High-Dimensional Data Using P-Trees
1 Decision Tree Induction is a powerful classification tool that is much used in practice and works well for static data with dozens of attributes. We adapt the decision tree conce...
Anne Denton, William Perrizo