Seeking multiple solutions: An updated survey on niching methods and their applications
Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …
in a single simulation run has practical relevance to problem solving across many fields …
Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study
The classification problem can be addressed by numerous techniques and algorithms which
belong to different paradigms of machine learning. In this paper, we are interested in …
belong to different paradigms of machine learning. In this paper, we are interested in …
[LIVRE][B] Data preprocessing in data mining
Data preprocessing is an often neglected but major step in the data mining process. The
data collection is usually a process loosely controlled, resulting in out of range values, eg …
data collection is usually a process loosely controlled, resulting in out of range values, eg …
[PDF][PDF] Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework
Data Mining (DM) is the process for automatic discovery of high level knowledge by
obtaining information from real world, large and complex data sets [26], and is the core step …
obtaining information from real world, large and complex data sets [26], and is the core step …
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability
The experimental analysis on the performance of a proposed method is a crucial and
necessary task to carry out in a research. This paper is focused on the statistical analysis of …
necessary task to carry out in a research. This paper is focused on the statistical analysis of …
A multi-objective genetic optimization of interpretability-oriented fuzzy rule-based classifiers
F Rudziński - Applied Soft Computing, 2016 - Elsevier
The paper presents a multi-objective genetic approach to design interpretability-oriented
fuzzy rule-based classifiers from data. The proposed approach allows us to obtain systems …
fuzzy rule-based classifiers from data. The proposed approach allows us to obtain systems …
Evolutionary multi-objective optimization in uncertain environments
CK Goh, KC Tan - Issues and Algorithms, Studies in Computational …, 2009 - Springer
Many real-world problems involve the simultaneous optimization of several competing
objectives and constraints that are difficult, if not impossible, to solve without the aid of …
objectives and constraints that are difficult, if not impossible, to solve without the aid of …
An interpretable classification rule mining algorithm
Obtaining comprehensible classifiers may be as important as achieving high accuracy in
many real-life applications such as knowledge discovery tools and decision support …
many real-life applications such as knowledge discovery tools and decision support …
An evolutionary framework for machine learning applied to medical data
Supervised learning problems can be faced by using a wide variety of approaches
supported in machine learning. In recent years there has been an increasing interest in …
supported in machine learning. In recent years there has been an increasing interest in …
Hybrid multiobjective evolutionary design for artificial neural networks
CK Goh, EJ Teoh, KC Tan - IEEE Transactions on Neural …, 2008 - ieeexplore.ieee.org
Evolutionary algorithms are a class of stochastic search methods that attempts to emulate
the biological process of evolution, incorporating concepts of selection, reproduction, and …
the biological process of evolution, incorporating concepts of selection, reproduction, and …