Desktop Survival Guide
by Graham Williams

Neural Network

> library(nnet)
> ?nnet		# See example there

Consider a two-class problem. Build a neural network with


The average Matthew Correlation Coeffience can be used to gauge the performance of the neural network. The highr the value the better.

For an unbalanced class, for example where the ratio of class A to class B is about 3:100, we might decide to weight the under-represented class:

> sample.nn <- nnet(....... weights=ifelse(ds$class=="A", 100/3, 1)

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