Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset

Algorithm 3

The indirect classification algorithm of Scenario 1.

Require: the target training set , the target testing set ,

 the auxiliary sample set , a base learning algorithm Learner

Ensure: classification function

 ;     / denote the feature vectors set of /

 ;    /  denote the target sample set/

 ;   / denote the feature vectors set of /

 ;    /constructing the MIDS/

 ;  /add the corresponding labels to the feature

             vectors of /

    / denotes the new training set/

 ;  / denotes the function implemented by a base

        learning algorithm trained on the new training set /