Active Learning to reduce the label complexity of classification in census income data
نویسنده
چکیده
Active Learning is an important branch of Machine Learning that tries to reduce the label complexity associated with the task of constructing classifiers. In this work, we apply two major active learning techniques to the U.S. census income data and demonstrate the superior label complexity of active learning over supervised learning.
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تاریخ انتشار 2013