original algo
QT:{{”
Initialize the weights. Weights may be initialized to 0 or to a small random value. In the example below, we use 0.
For each example j in our training set D, perform the following steps over the input xj and desired output dj:
Calculate the actual
output:yj(t)=f[w(t)⋅xj]=f[w0(t)xj,0+w1(t)xj,1+w2(t)xj,2+⋯+wn(t)xj,n] Update the weights:wi(t+1)=wi(t)+r⋅(dj−yj(t))xj,i, for all features 0≤i≤n, r is the learning rate.
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