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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Neural networks

After remaining a long time in academic circles due to their advanced mathematical background, neural networks (NN) rapidly grew in popularity as more practically usable formats are available – like the built-in function of R. NNs are artificial intelligence adaptive software that can detect complex patterns in data: it is just like an old trader who has a good market intuition but cannot always explain to you why he is convinced you should go short on the Dow Jones Industrial Average index (DIJA).

The network architecture consists of a number of nodes connected by links. Networks usually have 3 or 4 layers: input, hidden and output layers, and in each layer several neurons can be found. The number of first layer's nodes corresponds ...

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