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Characterization is a big data methodology that is used for generating descriptive parameters that effectively describe the characteristics and behavior of a particular data item. This is then used in unsupervised learning algorithms in order to find patterns, clusters and trends without incorporating class labels that may have biases. It has its uses in cluster analysis and even deep learning.
Big data characterization is a technique for transforming raw data into useful information, being used in machine learning algorithms and data mining. Characterization essentially generates condensed representations of whatever information content is hidden within data. Therefore, it can be used as a means of measuring and tracking events, changes and new emergent behaviors in large dynamic data streams.
Some benefits of characterization: