An Improved Semi-Supervised Clustering Algorithm Based on Active Learning

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Topic: Big Data
Format: PDF
In semi supervised clustering is one of the major tasks and aims at grouping the data objects into meaningful classes (clusters) such that the similarity of objects within clusters is maximized and the similarity of objects between clusters is minimized. The dataset sometimes may be in mixed nature that is it may consist of both numeric and categorical type of data. Naturally these two types of data may differ in their characteristics. Due to the differences in their characteristics in order to group these types of mixed data it is better to use the ensemble clustering method which uses split and merge approach to solve this problem.
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