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Evolutionary machine learning: A survey
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 …
problems in a stochastic manner. They can offer a reliable and effective approach to address …
kNN Classification: a review
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 …
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
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 …
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
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 …
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
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 …
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
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 …
performing recognition tasks. It has also demonstrated itself to be one of the most useful …
Forest optimization algorithm
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 …
continuous nonlinear optimization problems has been proposed. It is inspired by few trees in …
Genetic algorithms in feature and instance selection
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 …
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
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 …
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
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 …
quadrotor applied in the position control with the differential evolution algorithm (DE), which …