Attribute selection is a data preprocessing step which aims at identifying relevant attributes for the target machine learning task – namely classification in this paper. In this paper, we propose a new attribute selection strategy – based on a lazy learning approach – which postpones the identification of relevant attributes until an instance is submitted for classification. Our strategy relie...

Attribute Reduction has a significant role in different branches of artificial intelligence like machine learning, pattern recognition, data mining from databases etc. This paper deals with reduction of unimportant attribute(s) for classification and decision making, using Fuzzy-Rough set. A survey of Fuzzy-Rough set based methods for attribute reduction is presented here.

In computer image processing, traditional object classification methods focus on visual objects such as cars, dogs, and airplanes. However, these objects are not easy to scale, require extensive training for all classes, and are susceptible to unseen object classification failure. Recently, a new object classification approach called attribute-based object classification has been introduced by ...