Ranking really needs more liked / commented on events (positive examples) to be able to learn feature weights. Right now none of the features give good results with just 8 likes in the data set :(
Looking at the Iterative reweighting computation more, I could hack in weighting at the y-mu step and just see how it performs, I wouldn't be surprised if that would be correct (equivalent to repeating rows in the x matrix and y vector):
Logistic regression iteration step
https://en.wikipedia.org/wiki/Logistic_regression#Algorithm
mu = sigmoid(x*w)
s = diag(mu * (1 - mu))
wnew = (x' * s * x)^-1 * x' * (s * x * w + y - mu)
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