May 2020
Intermediate to advanced
530 pages
17h 8m
English
Content preview from Hands-On Machine Learning with C++
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Loss function definition
After we've defined the network structure, we need to define the loss function for the optimization algorithm. The ErrorFunction class is used for this purpose. Its constructor takes four parameters:
- An object representing the training dataset
- A pointer to the object that represents the network's structure
- A pointer to the object that implements the loss function—SquaredLoss, in our case
- A Boolean flag telling us to use mini-batches or not
The ErrorFunction type object can be configured with a regularizer. For example, we can instantiate the object of the TwoNormRegularizer class and call the setRegularizer method in the ErrorFunction type object with two parameters: the weight decay factor value and the pointer ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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