Angle Modulated Artificial Bee Colony Algorithms for Feature Selection

Abstract

Optimal feature subset selection is an important and a difficult task for pattern classification, data mining, and machine intelligence applications. The objective of the feature subset selection is to eliminate the irrelevant and noisy feature in order to select optimum feature subsets and increase accuracy. The large number of features in a dataset increases the computational complexity thus leading to performance degradation. In this paper, to overcome this problem, angle modulation technique is used to reduce feature subset selection problem to four-dimensional continuous optimization problem instead of presenting the problem as a high-dimensional bit vector. To present the effectiveness of the problem presentation with angle modulation and to determine the efficiency of the proposed method, six variants of Artificial Bee Colony (ABC) algorithms employ angle modulation for feature selection. Experimental results on six high-dimensional datasets show that Angle Modulated ABC algorithms improved the classification accuracy with fewer feature subsets.

Putting Continuous Metaheuristics to Work in Binary Search Spaces

“…Position of best global solution Best position of selected particle Previous velocity particle in [94], it was applied to binary problems. Artificial bee colony was applied to a feature selection in [95] and to binary problems in [96].…”

Sum-rate maximization for wireless seismic data acquisition systems

“…These variations are able to solve the binary problem at hand. 1) AMPSO: The AMPSO algorithm has proven efficiency, especially when the dimensionality of the binary vector is large [21]. The function given in (7), which is derived from anglemodulation theory, is optimized using PSO.…”

A Signal Timing Optimization in Traffic Management using ABC Algorithm

“…The ABC algorithm has application in field of computer science, electrical engineering, mechanical engineering and electronics engineering. Artificial bee colony algorithm applied for feature selection [12], multicast routing [13], single machine scheduling [14], balancing in assembly line [15], designing of controller [16] and to find solution of travelling salesman problem [17]. List of applications of ABC algorithm are endless, there are almost every field including engineering, science and management where ABC algorithm is in use with priority over other competitive optimization algorithm.…”