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Showing 1 to 2 of 2 for “"Penalized Log-likelihood Function"”.
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A Novel Penalized Log-likelihood Function for Class Imbalance Problem
<p>The log-likelihood function is the optimization objective in the maximum likelihood method for estimating models (e.g., logistic regression, neural network). However, its formulation is based on assumptions that the target classes are equally distributed and the overall accuracy is maximized, …
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Nonparametric smoothing in extreme value theory
… a Fisher scoring algorithm to maximize the penalized log-likelihood function. The approach provides a flexible framework for exploring smooth trends in sample extremes, with the benefit of balancing the trade-off between 'smoothness' and adherence to the underlying data by simply changing …