Bi-clustering continuous data with self-organizing map
نویسندگان
چکیده
منابع مشابه
NGTSOM: A Novel Data Clustering Algorithm Based on Game Theoretic and Self- Organizing Map
Identifying clusters is an important aspect of data analysis. This paper proposes a noveldata clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizingmap (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning(CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clusteringdata. Different ...
متن کاملClustering of Self-Organizing Map
In this paper, we present a new similarity measure for a clustering self-organizing map which will be reached using a new approach of hierarchical clustering. (1) The similarity measure is composed from two terms: weighted Ward distance and Euclidean distance weighted by neighbourhood function. (2) An algorithm inspired from artificial ants named AntTree will be used to cluster a self-organizin...
متن کاملSelf Organizing Map based Clustering Approach for Trajectory Data
Clustering algorithm for the moving or trajectory data provides new and helpful information. It has wide application on various location aware services. In this study the Self Organizing Map is used to form the cluster on trajectory data. The self-organizing map (SOM) is an important tool in exploratory phase of data mining. It projects input space on prototypes of a low-dimensional regular gri...
متن کاملSpatial Data Clustering based on Self Organizing Map
Recently, research area in neural network based spatial analysis have been receiving increasing attention in the last few years. There are number of reasons and the strongest appeal of Artificial Neural Network (ANN) is the suitability for machine learning in computational adaptivity. Machine learning in computational neural network consist of adjusting connection weights to improve the perform...
متن کاملClustering gene expression data using adaptive double self-organizing map.
This paper presents a novel clustering technique known as adaptive double self-organizing map (ADSOM). ADSOM has a flexible topology and performs clustering and cluster visualization simultaneously, thereby requiring no a priori knowledge about the number of clusters. ADSOM is developed based on a recently introduced technique known as double self-organizing map (DSOM). DSOM combines features o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2012
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-012-1047-6