Title of article :
A unifying view on dataset shift in classification
Author/Authors :
Moreno-Torres، نويسنده , , Jose G. and Raeder، نويسنده , , Troy and Alaiz-Rodrيguez، نويسنده , , Rocيo and Chawla، نويسنده , , Nitesh V. and Herrera، نويسنده , , Francisco، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
The field of dataset shift has received a growing amount of interest in the last few years. The fact that most real-world applications have to cope with some form of shift makes its study highly relevant. The literature on the topic is mostly scattered, and different authors use different names to refer to the same concepts, or use the same name for different concepts. With this work, we attempt to present a unifying framework through the review and comparison of some of the most important works in the literature.
Keywords :
Dataset shift , Data fracture , Differing training and test populations , Covariate shift , Sample selection bias , Non-stationary distributions , Changing environments
Journal title :
PATTERN RECOGNITION
Journal title :
PATTERN RECOGNITION