logistic regression - R - Stepwise random results -


if set seed before regression (logistic)

lr = glm(target ~ 1, family=binomial, data = x) set.seed(12345) lr = stepaic(lr, scope = f, family=binomial, data = x, k = 3) summary(lr)

i different results depending on seed different performance. 1 random part of algorithm? because in neural net result depends on first weights if have local minima, in logistic regression random part?

(since conceptual question didn't add reproducible example.)


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