CODEWITHSUNDEEP
encog
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Reputation: 8135

Understanding the result from Encog neural network example

I'm playing around with encog 3.2 for java. From the example (http://www.heatonresearch.com/wiki/Hello_World), I make my own network with 4 neutrons in input layers and 2 neutrons in output layer.

1.0,1.0, actual=0.22018401281844316,ideal=1.0
-1.0,-1.0, actual=0.9903002141301814,ideal=0.0

Can someone explain to me how can I understand the result(actual vs ideal and those numbers before them..)
Thank you very much.

Upvotes: 1

Views: 212

Answers (1)

andrelucas
andrelucas

Reputation: 688

Note that at this stage, the network has been trained, and you are now in the testing stage.

The network has 2 inputs neurons and 1 output neuron.

The first two numbers in your result are given to the trained network as the inputs. Using the internal weights and biases (which are not changed during testing) it computes the result / output ... listed as actual.
ideal is what the result should be, ie the number listed in the dataset for that sample/row.

Generally when you want a 0 or 1 output (eg one of n) you will round the actual result.
So in this case the network computes

1 XOR 1 = 0.22, (rounded = 0) which is wrong (according to ideal).
-1 XOR -1 = 0.99, (rounded = 1) which is also wrong

Upvotes: 1

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