feedforward-neural-networks
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how to decide how many nodes are in the output layer?
from the tests, it seems that we have one output node
I believe (not sure) that the test called 'big case' has two output nodes. Here is the features/labels used :
var trainingSet = [[1, 1], [1, 2], [2, 1], [2, 2], [3, 1], [1, 3], [1, 4], [4, 1],
[6, 1], [6, 2], [6, 3], [6, 4], [6, 5], [5, 5], [4, 5], [3, 5]];
var predictions = [[1, 0], [1, 0], [1, 0], [1, 0], [1, 0], [1, 0], [1, 0], [1, 0],
[0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1]];
But I will add a test case to check that.