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Concerning Example 8, there is one more problem:
At the very end, when doing predictions with the parallel version, the following gives an error:
bm_parallel <- predict(get.best.model(result_parallel), df[,-1],link = function(x)(1/(1+exp(-x))))
mean(round(bm_parallel)==df$y)
Error in x.precalc %*% object$coefs[object$coefs != 0] :
non-conformable arguments
Can you look into this?
Prediction based on the mpm model works.
mpm_parallel <- predict(get.mpm.model(result = result_parallel,family = "binomial",y = df$y,x=df[,-1]), df[,-1],link = function(x)(1/(1+exp(-x))))
mean(round(mpm_parallel)==df$y)
and check MPM documentation for the value
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