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» Mining Several Data Bases with an Ensemble of Classifiers
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ICTAI
2006
IEEE
14 years 1 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
KDD
1995
ACM
109views Data Mining» more  KDD 1995»
13 years 11 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani
SIGKDD
2000
231views more  SIGKDD 2000»
13 years 7 months ago
KDD-99 Classifier Learning Contest: LLSoft's Results Overview
Kernel Miner is a new data-mining tool based on building the optimal decision forest. The tool won second place in the KDD'99 Classifier Learning Contest, August 1999. We des...
Itzhak Levin
ESWA
2008
128views more  ESWA 2008»
13 years 7 months ago
Mining the data from a hyperheuristic approach using associative classification
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
Fadi A. Thabtah, Peter I. Cowling
ICDM
2002
IEEE
109views Data Mining» more  ICDM 2002»
14 years 20 days ago
Using Text Mining to Infer Semantic Attributes for Retail Data Mining
Current Data Mining techniques usually do not have a mechanism to automatically infer semantic features inherent in the data being “mined”. The semantics are either injected i...
Rayid Ghani, Andrew E. Fano