Hybrid Clustering and Classification Using Weighted K Mean, Neural Networks and SVM

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Provided by: Creative Commons
Topic: Data Management
Format: PDF
Clustering is very helpful in the analysis of raw data. As the clustering is unsupervised learning technique so in order to optimize the results, the authors use classifier with clustering. This paper proposes hybrid technique in which weighted k mean is used for clustering whereas neural networks and SVM are used as classifiers. Weighted k mean results in unlabelled data by calculating the feature weights of clusters. Neural networks and SVM will label the unlabelled data as they have the ability to recognize the patterns.
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