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ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
13 years 10 months ago
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kerneldensity-based clustering with pixel-oriented displays to emphasize c...
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...
ICDM
2003
IEEE
109views Data Mining» more  ICDM 2003»
13 years 10 months ago
Comparing Pure Parallel Ensemble Creation Techniques Against Bagging
We experimentally evaluate randomization-based approaches to creating an ensemble of decision-tree classifiers. Unlike methods related to boosting, all of the eight approaches co...
Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfi...
ICDM
2003
IEEE
98views Data Mining» more  ICDM 2003»
13 years 10 months ago
On the Privacy Preserving Properties of Random Data Perturbation Techniques
Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving data mining techniques. A large...
Hillol Kargupta, Souptik Datta, Qi Wang, Krishnamo...
ICDM
2003
IEEE
105views Data Mining» more  ICDM 2003»
13 years 10 months ago
SVM Based Models for Predicting Foreign Currency Exchange Rates
Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA bas...
Joarder Kamruzzaman, Ruhul A. Sarker, Iftekhar Ahm...
ICDM
2003
IEEE
99views Data Mining» more  ICDM 2003»
13 years 10 months ago
Scalable Model-based Clustering by Working on Data Summaries
The scalability problem in data mining involves the development of methods for handling large databases with limited computational resources. In this paper, we present a two-phase...
Huidong Jin, Man Leung Wong, Kwong-Sak Leung
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
13 years 10 months ago
Validating and Refining Clusters via Visual Rendering
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
Keke Chen, Ling Liu
ICDM
2003
IEEE
115views Data Mining» more  ICDM 2003»
13 years 10 months ago
Icon-based Visualization of Large High-Dimensional Datasets
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional d...
Ping Chen, Chenyi Hu, Wei Ding 0003, Heloise Lynn,...
ICDM
2003
IEEE
130views Data Mining» more  ICDM 2003»
13 years 10 months ago
Information Theoretic Clustering of Sparse Co-Occurrence Data
A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory which minimizes the resulting loss in mutual information. A divisive cl...
Inderjit S. Dhillon, Yuqiang Guan
ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
13 years 10 months ago
Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery...
Mukund Deshpande, Michihiro Kuramochi, George Kary...
ICDM
2003
IEEE
100views Data Mining» more  ICDM 2003»
13 years 10 months ago
Towards Simple, Easy-to-Understand, yet Accurate Classifiers
Doina Caragea, Dianne Cook, Vasant Honavar