Content Classification Using Active Learning Approach
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Text classification methodologies are utilized broadly to understand genuine difficulties. The failure and success of classification grouping frameworks is based on the datasets used to prepare them; without a decent dataset it is difficult to fabricate a quality framework. This work looks at the different approaches of active learning characterization for data labeling. First, we have defined different selection algorithms that can be used for labeling the data. Second, we compared the result of normal classification algorithm and active learning algorithm.
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