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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/141012
Regularization of a neural network for binary classification
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Neural networks are complex non-linear models used to learn representations of data with multiple
levels of abstraction. In this work, we introduce the basic notions of a neural network model, explaining the training process and generalization capabilities. In particular, to avoid overfitting to the training data, we study the L2 regularization method. Finally, an application of 2D vector classification has been developed to illustrate the concepts
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Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2019, Tutora: M. Ángeles Serrano Moral
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BÉCARES MAS, Andreu. Regularization of a neural network for binary classification. [consulted: 12 of October of 2026]. Available at: https://hdl.handle.net/2445/141012