Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pareto Efficient Multi Objective Optimization for Local Tuning of
  Analogy Based Estimation   Analogy Based Effort Estimation (ABE) is one of the prominent methods for
software effort estimation. The fundamental concept of ABE is closer to the
mentality of expert estimation but with an automated procedure in which the
final estimate is generated by reusing similar historical projects. The main
key issue when using ABE is how to adapt the effort of the retrieved nearest
neighbors. The adaptation process is an essential part of ABE to generate more
successful accurate estimation based on tuning the selected raw solutions,
using some adaptation strategy. In this study we show that there are three
interrelated decision variables that have great impact on the success of
adaptation method: (1) number of nearest analogies (k), (2) optimum feature set
needed for adaptation, and (3) adaptation weights. To find the right decision
regarding these variables, one need to study all possible combinations and
evaluate them individually to select the one that can improve all prediction
evaluation measures. The existing evaluation measures usually behave
differently, presenting sometimes opposite trends in evaluating prediction
methods. This means that changing one decision variable could improve one
evaluation measure while it is decreasing the others. Therefore, the main theme
of this research is how to come up with best decision variables that improve
adaptation strategy and thus, the overall evaluation measures without degrading
the others. The impact of these decisions together has not been investigated
before, therefore we propose to view the building of adaptation procedure as a
multi-objective optimization problem. The Particle Swarm Optimization Algorithm
(PSO) is utilized to find the optimum solutions for such decision variables
based on optimizing multiple evaluation measures

12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin