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» Distributed Data Mining vs. Sampling Techniques: A Compariso...
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SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
13 years 9 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
EUROPAR
2009
Springer
14 years 9 days ago
Detailed Performance Analysis Using Coarse Grain Sampling
Performance evaluation tools enable analysts to shed light on how applications behave both from a general point of view and at concrete execution points, but cannot provide detaile...
Harald Servat, Germán Llort, Judit Gimenez,...
PROMISE
2010
13 years 2 months ago
Case-based reasoning vs parametric models for software quality optimization
Background: There are many data mining methods but few comparisons between them. For example, there are at least two ways to build quality optimizers, programs that find project o...
Adam Brady, Tim Menzies
ICDE
2006
IEEE
165views Database» more  ICDE 2006»
14 years 1 months ago
Privacy Preserving Clustering on Horizontally Partitioned Data
Data mining has been a popular research area for more than a decade due to its vast spectrum of applications. The power of data mining tools to extract hidden information that can...
Ali Inan, Yücel Saygin, Erkay Savas, Ay&ccedi...
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
13 years 9 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu