Dataset Shift in Machine Learning

An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions. Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs between training and test stages. Covariate shift, a particular case of dataset shift, occurs when only the input distribution changes. Dataset shift is present in most practical applications, for reasons ranging from the bias introduced by experimental design to the irreproducibility of the testing conditions at training time. (An example is -email spam filtering, which may fail to recognize spam…

• AG
  Australian Government
• DF
  Deutsche Forschungsgemeinschaft
• MO
  Ministry of Education, Culture, Sports, Science and Technology
• BF
  Bundesministerium für Bildung und Forschung
• L
  Lundbeckfonden
• HL
  H. Lundbeck A/S