A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is compared with existing clustering Techniques such as K-Means clustering, Hierarchical clustering and SOM Clustering. The proposed technique is used to cluster an Earthquake dataset and the performance is compared with the other existing clustering technique. The experimental results show that the proposed clustering method demonstrated better results as compared to other clustering methods
International audienceIn this paper, we propose a new clustering method consisting in automated “flo...
Abstract- The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by ...
Clustering partitions a set of objects into non-overlapping subsets called clusters such that object...
A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is ...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
International audienceSelf-Organizing Map (SOM) is an artificial neural network tool that is trained...
AbstractSelf-organizing map (SOM) is one of the most popular neural network methods for cluster anal...
The clustering results are analyzed by comparing two algorithms (SOM and FCM). The multidimensional...
Data clustering is an important and widely used task of data mining that groups similar items togeth...
This study identifies the results of some test results clustering methods. The data set used in this...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
This study identifies the results of some test results clustering methods. The data set used in this...
This paper proposes a clustering algorithm based on the Self Organizing Map (SOM) method. To find th...
This study identifies the results of some test results clustering methods. The data set used in this...
International audienceIn this paper, we propose a new clustering method consisting in automated “flo...
Abstract- The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by ...
Clustering partitions a set of objects into non-overlapping subsets called clusters such that object...
A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is ...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
International audienceSelf-Organizing Map (SOM) is an artificial neural network tool that is trained...
AbstractSelf-organizing map (SOM) is one of the most popular neural network methods for cluster anal...
The clustering results are analyzed by comparing two algorithms (SOM and FCM). The multidimensional...
Data clustering is an important and widely used task of data mining that groups similar items togeth...
This study identifies the results of some test results clustering methods. The data set used in this...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
This study identifies the results of some test results clustering methods. The data set used in this...
This paper proposes a clustering algorithm based on the Self Organizing Map (SOM) method. To find th...
This study identifies the results of some test results clustering methods. The data set used in this...
International audienceIn this paper, we propose a new clustering method consisting in automated “flo...
Abstract- The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by ...
Clustering partitions a set of objects into non-overlapping subsets called clusters such that object...