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DATE 2017-03-01

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MESSAGE
DATE 2017-03-29
FROM Ruben Safir
SUBJECT Subject: [Learn] This is hard to understand what the logic is here
From learn-bounces-at-nylxs.com Wed Mar 29 01:31:31 2017
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There is a bias included here.
The bias is treated as a weight corresponding to a "pseudo" input that
is always 1. So for a perceptron with 2 regular inputs, the weight
vector will have size 3.

That while loop just appends ones to the input vector until it's big
enough to do a dot product of the inputs and weights.
The step function returns 0 or 1 but represents them as float because we
might want to substitute a different function, such as sigmoid, which
would need floats.
CL

-----Original Message-----
From: Ruben Safir
To: Christopher League , "learn-at-nylxs.com"

Sent: Wed, 29 Mar 2017 1:16
Subject: This is hard to understand what the logic is here

float feed_forward(const perceptron& p, vector& input)
{
// If input size doesn't match, add "bias" inputs:
while(input.size() < p.weights.size()) {
input.push_back(1);
}
return step_function(p.threshold, dot_product(p.weights, input));
}


step_function should return an INT

What is the logic to this? Don't you always need the bias?

https://gitlab.liu.edu/cs691s17/public/raw/1dd68b2f00b96db17a988242221f50e4eab7ddbb/perceptrons/perceptrons.cpp

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