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CLASSIFICATION AND PREDICTION - Universität Wien

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Peter Brezany Institut für Softwarewissenschaft, WS 2002 6<br />

What Is a Neural Net?<br />

NN consists of basic units modeled on the principles of biological neurons. These units are<br />

connected together as shown in the next figures.<br />

Slide 11<br />

input 1<br />

input 2<br />

input 3<br />

input 4<br />

output<br />

output<br />

output<br />

1<br />

2<br />

3<br />

A neural network can produce<br />

multiple output values.<br />

What Is a Neural Net? (2)<br />

input 1<br />

input 2<br />

input 3<br />

input 4<br />

output<br />

A very simple neural network<br />

takes four inputs and produces an<br />

output. The result of training this<br />

network is exactly equivalent to<br />

the statistical technique called<br />

logistic regression.<br />

Slide 12<br />

input 1<br />

input 2<br />

input 3<br />

input 4<br />

output<br />

This network has a middle layer<br />

called the hidden layer.The<br />

hidden layer makes the network<br />

more powerful by enabling it to<br />

recognize more patterns.<br />

input 1<br />

input 2<br />

input 3<br />

output<br />

Increasing the size of the hidden<br />

layer makes the network more<br />

powerful but introduces the risk of<br />

overfitting. Usually, only one<br />

hidden layer is needed.<br />

input 4

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