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JMLR
2010
118views more  JMLR 2010»
15 years 1 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
CIKM
2011
Springer
14 years 6 months ago
Content based social behavior prediction: a multi-task learning approach
The study of information flow analyzes the principles and mechanisms of social information distribution. It is becoming an extremely important research topic in social network re...
Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Ju...
CEC
2008
IEEE
16 years 1 months ago
DCA for bot detection
Abstract— Ensuring the security of computers is a nontrivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emer...
Yousof Al-Hammadi, Uwe Aickelin, Julie Greensmith
ACL
2008
15 years 8 months ago
Assessing the Costs of Sampling Methods in Active Learning for Annotation
Traditional Active Learning (AL) techniques assume that the annotation of each datum costs the same. This is not the case when annotating sequences; some sequences will take longe...
Robbie Haertel, Eric K. Ringger, Kevin D. Seppi, J...
ML
2010
ACM
127views Machine Learning» more  ML 2010»
15 years 5 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby