Siddheswar Ray

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The main disadvantage of the k-means algorithm is that the number of clusters, K, must be supplied as a parameter. In this paper we present a simple validity measure based on the intra-cluster and inter-cluster distance measures which allows the number of clusters to be determined automatically. The basic procedure involves producing all the segmented(More)
This paper considers a criterion for selection of moving average (MA) time series models based upon the information-theoretic principle of minimum message length (MML). We derive an MML model selection criterion for invertible MA time series models using the Wallace and Freeman (1987) MML approximation, MML87. The MML model order selection performance is(More)
Clustering is technique which is used to analyze the data in efficient manner and generate required information. To cluster the dataset, there is a technique named k-mean, is applied which is based on central point selection and calculation of Euclidian Distance. Here in k-mean, dataset will be loaded and from the dataset. Central points are selected using(More)
Ideally computer pattern recognition systems should be insensitive to scaling, translation, distortion and rotation. Many neural network models have been proposed to address this purpose. The Neocognitron is a multi-layered neural network model for pattern recognition introduced by Fukushima in the early 1980s. It was considered effective and, after(More)
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