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ICML
2004
IEEE
14 years 11 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
WSC
2008
14 years 13 days ago
Restricted subset selection
This paper develops procedures for selecting a set of normal populations with unknown means and unknown variances in order that the final subset of selected populations satisfies ...
E. Jack Chen
JAMDS
2002
107views more  JAMDS 2002»
13 years 9 months ago
Estimating a resource selection function with line transect sampling
Abstract. A resource selection probability function is a function that gives the probability that a resource unit (e.g., a plot of land) that is described by a set of habitat varia...
Bryan F. J. Manly
ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
14 years 3 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani
CACM
2008
53views more  CACM 2008»
13 years 10 months ago
Distributed selection: a missing piece of data aggregation
In this article, we study the problem of distributed selection from a theoretical point of view. Given a general connected graph of diameter D consisting of n nodes in which each ...
Fabian Kuhn, Thomas Locher, Roger Wattenhofer