SOM-based algorithms for qualitative variables
نویسندگان
چکیده
منابع مشابه
SOM-based algorithms for qualitative variables
It is well known that the SOM algorithm achieves a clustering of data which can be interpreted as an extension of Principal Component Analysis, because of its topology-preserving property. But the SOM algorithm can only process real-valued data. In previous papers, we have proposed several methods based on the SOM algorithm to analyze categorical data, which is the case in survey data. In this ...
متن کاملInvited article SOM-based algorithms for qualitative variables
It is well known that the SOM algorithm achieves a clustering of data which can be interpreted as an extension of Principal Component Analysis, because of its topologypreserving property. But the SOM algorithm can only process real-valued data. In previous papers, we have proposed several methods based on the SOM algorithm to analyze categorical data, which is the case in survey data. In this p...
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The Kohonen self-organizing map (SOM) is an unsupervised neural network with a competitive learning strategy that uses a neighborhood lateral interaction function to discover the hidden topological structure of the input data and has both visualization and clustering properties. In this presentation, we propose batch SOM algorithms with automatic weighting of the variables to training the Kohon...
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Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM has been applied in the study of complex problems such as vector quantizations, combinatorial optimization, and pattern recognition. This paper proposes a new usage of SOM as a tool for schema transformation hoping to achieve mo...
متن کاملSOM algorithms and their stability consideration
A two layered feedforward neural network is considered as Kohonen’s dot-product type SOM model which defines a winner function f from an input pattern set into an output unit set. It defines pattern classifiers through step by step self-organization. What kinds of classifiers they can ultimately be and how they are attained asymptotically are the basic problems to be solved. Our main result is ...
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ژورنال
عنوان ژورنال: Neural Networks
سال: 2004
ISSN: 0893-6080
DOI: 10.1016/j.neunet.2004.07.010