November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Model parameters
There is no best practice or recommended rule or policy that will tell the data scientist how many layers and/or nodes to use (although there are several more or less industry--accepted rules) in an artificial neural network model.
Customarily, if at all necessary, one hidden layer is enough for most or, a vast number of, artificial neural network statistical applications (although you may have observed that we showed three hidden layers in our graphical image at the beginning of this chapter).
As far as the number of nodes, the number should frequently be between the input layer size and the output layer size, usually 2/3 of the input size.
Bottom line—when the data scientist is determining the number of layers and nodes ...
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