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» Mining Several Data Bases with an Ensemble of Classifiers
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SDM
2007
SIAM
131views Data Mining» more  SDM 2007»
13 years 9 months ago
Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
Yijian Bai, Haixun Wang, Carlo Zaniolo
SDM
2007
SIAM
140views Data Mining» more  SDM 2007»
13 years 9 months ago
A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions
In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but...
Jing Gao, Wei Fan, Jiawei Han, Philip S. Yu
DMIN
2009
144views Data Mining» more  DMIN 2009»
13 years 5 months ago
Fish or Shark - Data Mining Online Poker
In this paper, data mining techniques are used to analyze data gathered from online poker. The study focuses on short-handed Texas Hold'em, and the data sets used contain thou...
Ulf Johansson, Cecilia Sönströd
ICDE
1999
IEEE
209views Database» more  ICDE 1999»
14 years 9 months ago
Parallel Classification for Data Mining on Shared-Memory Multiprocessors
We present parallel algorithms for building decision-tree classifiers on shared-memory multiprocessor (SMP) systems. The proposed algorithms span the gamut of data and task parall...
Mohammed Javeed Zaki, Ching-Tien Ho, Rakesh Agrawa...
IJCNN
2007
IEEE
14 years 2 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar