I am new to Machine Learning and I am trying analyze the classification algorithm for a project of mine. I came across SGDClassifier
in sklearn
library. But a lot of papers have referred to SGD as an optimization technique. Can someone please explain how is SGDClassifier
implemented?
Taken from SGD sikit-learn documentation
loss="hinge"
: (soft-margin) linear Support Vector Machine,
loss="modified_huber"
: smoothed hinge loss,
loss="log"
: logistic regression