TYPES OF COST IN INDUCTIVE CONCEPT LEARNING PETER

Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 10, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: M.MOHANA SUBASINI

Reference:IJCS-202

View PDF Format

Abstract

Inductive concept learning is the task of learning to assign cases to a discrete set of classes. In real-world applications of concept learning, there are many different types of cost involved. The majority of the machine learning literature ignores all types of cost (unless accuracy is interpreted as a type of cost measure). A few papers have investigated the cost of misclassification errors. Very few papers have examined the many other types of cost. In this paper, we attempt to create a taxonomy of the different types of cost that are involved in inductive concept learning. This taxonomy may help to organize the literature on cost-sensitive learning. We hope that it will inspire researchers to investigate all types of cost in inductive concept learning in more depth.

References

No References


Keywords

No Keywords

This work is licensed under a Creative Commons Attribution 3.0 Unported License.   

TOP
Facebook IconYouTube IconTwitter IconVisit Our Blog