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Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they… Expand Deep neural nets with a large number of parameters are very powerful machine learning systems. However, overfitting is a serious… Expand Aim
Models of species niches and distributions have become invaluable to biogeographers over the past decade, yet several… Expand Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being… Expand This paper addresses a common methodological flaw in the comparison of variable selection methods. A practical approach to guide… Expand The conventional wisdom is that backprop nets with excess hidden units generalize poorly. We show that nets with excess capacity… Expand The application of feed forward back propagation artificial neural networks with one hidden layer (ANN) to perform the equivalent… Expand A central problem in machine learning is supervised learning—that is, learning from labeled training data. For example, a… Expand In the wrapper approach to feature subset selection, a search for an optimal set of features is made using the induction… Expand We study the characteristics of learning with ensembles. Solving exactly the simple model of an ensemble of linear students, we… Expand