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» Assessing data mining results via swap randomization
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KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 6 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
ICDM
2007
IEEE
136views Data Mining» more  ICDM 2007»
13 years 12 months ago
Recommendation via Query Centered Random Walk on K-Partite Graph
This paper presents a recommendation algorithm that performs a query dependent random walk on a k-partite graph constructed from the various features relevant to the recommendatio...
Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William...
KDD
2008
ACM
264views Data Mining» more  KDD 2008»
14 years 6 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo
ICANN
2010
Springer
13 years 6 months ago
Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap
Structural equation models have been widely used to study causal relationships between continuous variables. Recently, a non-Gaussian method called LiNGAM was proposed to discover ...
Yusuke Komatsu, Shohei Shimizu, Hidetoshi Shimodai...
SDM
2012
SIAM
278views Data Mining» more  SDM 2012»
11 years 8 months ago
Legislative Prediction via Random Walks over a Heterogeneous Graph
In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic