H.6.3.1. Classifier design and evaluation
1. Ensemble-based Top-k Recommender System Considering Incomplete Data

M. Moradi; J. Hamidzadeh

Volume 7, Issue 3 , Summer 2019, , Pages 393-402

http://dx.doi.org/10.22044/jadm.2019.7026.1830

Abstract
  Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ...  Read More

H.6. Pattern Recognition
2. IRDDS: Instance reduction based on Distance-based decision surface

J. Hamidzadeh

Volume 3, Issue 2 , Summer 2015, , Pages 121-130

http://dx.doi.org/10.5829/idosi.JAIDM.2015.03.02.01

Abstract
  In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, ...  Read More