Selecting Efficient Features via a Hyper-Heuristic Approach

01/20/2016
by   Mitra Montazeri, et al.
0

By Emerging huge databases and the need to efficient learning algorithms on these datasets, new problems have appeared and some methods have been proposed to solve these problems by selecting efficient features. Feature selection is a problem of finding efficient features among all features in which the final feature set can improve accuracy and reduce complexity. One way to solve this problem is to evaluate all possible feature subsets. However, evaluating all possible feature subsets is an exhaustive search and thus it has high computational complexity. Until now many heuristic algorithms have been studied for solving this problem. Hyper-heuristic is a new heuristic approach which can search the solution space effectively by applying local searches appropriately. Each local search is a neighborhood searching algorithm. Since each region of the solution space can have its own characteristics, it should be chosen an appropriate local search and apply it to current solution. This task is tackled to a supervisor. The supervisor chooses a local search based on the functional history of local searches. By doing this task, it can trade of between exploitation and exploration. Since the existing heuristic cannot trade of between exploration and exploitation appropriately, the solution space has not been searched appropriately in these methods and thus they have low convergence rate. For the first time, in this paper use a hyper-heuristic approach to find an efficient feature subset. In the proposed method, genetic algorithm is used as a supervisor and 16 heuristic algorithms are used as local searches. Empirical study of the proposed method on several commonly used data sets from UCI data sets indicates that it outperforms recent existing methods in the literature for feature selection.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/17/2023

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

In this paper, a new feature selection algorithm, called SFE (Simple, Fa...
research
03/01/2023

A Hybrid Genetic Algorithm with Type-Aware Chromosomes for Traveling Salesman Problems with Drone

There are emerging transportation problems known as the Traveling Salesm...
research
09/02/2020

A new heuristic algorithm for fast k-segmentation

The k-segmentation of a video stream is used to partition it into k piec...
research
04/02/2020

Trustless parallel local search for effective distributed algorithm discovery

Metaheuristic search strategies have proven their effectiveness against ...
research
11/21/2018

Improving PSO Global Method for Feature Selection According to Iterations Global Search and Chaotic Theory

Making a simple model by choosing a limited number of features with the ...
research
02/02/2022

Flipping the switch on local exploration: Genetic Algorithms with Reversals

One important feature of complex systems are problem domains that have m...
research
02/09/2012

Hyper heuristic based on great deluge and its variants for exam timetabling problem

Today, University Timetabling problems are occurred annually and they ar...

Please sign up or login with your details

Forgot password? Click here to reset