Add to ORKGIn this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications
Clustering is an unsupervised learning technique used in data mining for finding groups with increas...
101 p.Clustering represents a core research area of machine learning. It has been widely used in dat...
There has been a growing interest in data mining in several AI-related areas, including evolutionary...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolution...
This paper elaborates on the improvement of an evolutionary algorithm for clustering (EAC) introduce...
In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm eff...
Data clustering consists in finding homogeneous groups in a dataset. The importance attributed to cl...
Data mining is the process of deriving knowledge from data. The data clustering is a classical activ...
The modern world has witnessed a surge in technological advancements that span various industries. I...
This PHD thesis deals with the evolutionary algorithms for mining frequent patterns and discovering ...
One of the top ten most influential data mining algorithms, k-means, is known for being simple and s...
Recent years, data mining techniques have been developed for extracting rules from big data. However...
In the cluster analysis most of the existing clustering techniques for clustering, accept the number...
This paper pursues a course of investigation of an approach to combine Evolutionary Computation and ...
Clustering is an unsupervised learning technique used in data mining for finding groups with increas...
101 p.Clustering represents a core research area of machine learning. It has been widely used in dat...
There has been a growing interest in data mining in several AI-related areas, including evolutionary...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolution...
This paper elaborates on the improvement of an evolutionary algorithm for clustering (EAC) introduce...
In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm eff...
Data clustering consists in finding homogeneous groups in a dataset. The importance attributed to cl...
Data mining is the process of deriving knowledge from data. The data clustering is a classical activ...
The modern world has witnessed a surge in technological advancements that span various industries. I...
This PHD thesis deals with the evolutionary algorithms for mining frequent patterns and discovering ...
One of the top ten most influential data mining algorithms, k-means, is known for being simple and s...
Recent years, data mining techniques have been developed for extracting rules from big data. However...
In the cluster analysis most of the existing clustering techniques for clustering, accept the number...
This paper pursues a course of investigation of an approach to combine Evolutionary Computation and ...
Clustering is an unsupervised learning technique used in data mining for finding groups with increas...
101 p.Clustering represents a core research area of machine learning. It has been widely used in dat...
There has been a growing interest in data mining in several AI-related areas, including evolutionary...