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193
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SDM
2009
SIAM
343views Data Mining» more  SDM 2009»
16 years 3 months ago
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
Masashi Sugiyama, Yoshinobu Kawahara
ICDM
2007
IEEE
103views Data Mining» more  ICDM 2007»
16 years 14 days ago
An Examination of Experimental Methodology for Classifiers of Relational Data
Experimental methodology for evaluating classification algorithms in relational (i.e., networked) data is complicated by dependencies between related data instances. We survey the...
Brian Gallagher, Tina Eliassi-Rad
ICIC
2005
Springer
15 years 11 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao
152
Voted
ICDM
2003
IEEE
130views Data Mining» more  ICDM 2003»
15 years 11 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
158
Voted
WAIM
2009
Springer
15 years 10 months ago
Intervention Events Detection and Prediction in Data Streams
Abstract. Mining interesting patterns in data streams has attracted special attention recently. This study revealed the principles behind observations, through variation of interve...
Yue Wang, Changjie Tang, Chuan Li, Yu Chen, Ning Y...