Evolutionary machine learning: A survey

A Telikani, A Tahmassebi, W Banzhaf… - ACM Computing …, 2021‏ - dl.acm.org
Evolutionary Computation (EC) approaches are inspired by nature and solve optimization
problems in a stochastic manner. They can offer a reliable and effective approach to address …

kNN Classification: a review

PK Syriopoulos, NG Kalampalikis, SB Kotsiantis… - Annals of Mathematics …, 2023‏ - Springer
The k-nearest neighbors (k/NN) algorithm is a simple yet powerful non-parametric classifier
that is robust to noisy data and easy to implement. However, with the growing literature on …

A survey of evolutionary computation for association rule mining

A Telikani, AH Gandomi, A Shahbahrami - Information Sciences, 2020‏ - Elsevier
Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data

I Triguero, D García‐Gil, J Maillo… - … : Data Mining and …, 2019‏ - Wiley Online Library
The k‐nearest neighbors algorithm is characterized as a simple yet effective data mining
technique. The main drawback of this technique appears when massive amounts of data …

Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

S García, J Luengo, F Herrera - Knowledge-Based Systems, 2016‏ - Elsevier
Data preprocessing is a major and essential stage whose main goal is to obtain final data
sets that can be considered correct and useful for further data mining algorithms. This paper …

Prototype selection for nearest neighbor classification: Taxonomy and empirical study

S Garcia, J Derrac, J Cano… - IEEE transactions on …, 2012‏ - ieeexplore.ieee.org
The nearest neighbor classifier is one of the most used and well-known techniques for
performing recognition tasks. It has also demonstrated itself to be one of the most useful …

Forest optimization algorithm

M Ghaemi, MR Feizi-Derakhshi - Expert systems with applications, 2014‏ - Elsevier
In this article, a new evolutionary algorithm, Forest Optimization Algorithm (FOA), suitable for
continuous nonlinear optimization problems has been proposed. It is inspired by few trees in …

Genetic algorithms in feature and instance selection

CF Tsai, W Eberle, CY Chu - Knowledge-Based Systems, 2013‏ - Elsevier
Feature selection and instance selection are two important data preprocessing steps in data
mining, where the former is aimed at removing some irrelevant and/or redundant features …

MRPR: A MapReduce solution for prototype reduction in big data classification

I Triguero, D Peralta, J Bacardit, S García, F Herrera - neurocomputing, 2015‏ - Elsevier
In the era of big data, analyzing and extracting knowledge from large-scale data sets is a
very interesting and challenging task. The application of standard data mining tools in such …

Attitude control of a quadrotor using PID controller based on differential evolution algorithm

A Gün - Expert Systems with Applications, 2023‏ - Elsevier
In this study, an energy efficiency study has been carried out through the moment values of a
quadrotor applied in the position control with the differential evolution algorithm (DE), which …