Fuzzy C-Means Two-Level Variable Weighting Clustering Algorithm For Multiview Data

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Provided by: Creative Commons
Topic: Big Data
Format: PDF
In clustering, the multi-view data is considered with two levels of variables as the view differences and the importance of individual variables in each view are taken into account. Existing system TW k-means, an automated two-level variable weighting clustering algorithm for multi-view data, which simultaneously compute weights for views and individual variables. In TW k-means, a view weight is assigned to each view to identify the compactness of the view and a variable weight is assigned to each variable to identify the importance of the variable. Both view and variable weights are used in the distance function to determine the clusters of objects.
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