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Browsing by Subject "logistic regression"

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Browsing by Subject "logistic regression"

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  • Oregon State University. Dept. of Computer Science; Restificar, Angelo C.; Dietterich, Thomas Glen (Corvallis, OR : Oregon State University, Dept. of Computer Science, 2013-01-29)
    An important challenge in machine learning is to find ways of learning quickly from very small amounts of training data. The only way to learn from small data samples is to constrain the learning process by exploiting ba ...
  • Oberst, Ian (2010-08-06)
    In text classification, labeling features is often less time consuming than labeling entire documents. In situations where very little labeled training data is available, feature relevance feedback has the potential to d ...

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