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137
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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
126
Voted
COLT
2004
Springer
15 years 6 months ago
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
129
Voted
ILP
2000
Springer
15 years 6 months ago
Decomposing Probability Distributions on Structured Individuals
Naive Bayesian classifiers have been very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribu...
Peter A. Flach, Nicolas Lachiche
111
Voted
CCIA
2008
Springer
15 years 4 months ago
On the Dimensions of Data Complexity through Synthetic Data Sets
Abstract. This paper deals with the characterization of data complexity and the relationship with the classification accuracy. We study three dimensions of data complexity: the len...
Núria Macià, Ester Bernadó-Ma...
107
Voted
PAMI
1998
127views more  PAMI 1998»
15 years 2 months ago
The Random Subspace Method for Constructing Decision Forests
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Tin Kam Ho