Logistic Regression in ML

https://open.spotify.com/episode/0ptTtCVLeuTNAtbRyzoDIV?si=a81aDcyYRsqUMGWbYt_GMQ&dl_branch=1

Logistic regression is a very robust machine learning technique which can be used in three modes: binary, multinomial and ordinal. We talk about assumptions and some misconceptions. For example, people believe that because logistic regression fits only a linear separator in the expanded dimensional space it wouldn’t be able to fit a complex boundary in the original space. Also, people normally use either linear regression or multinomial logistic regression when they should be using ordinal logistic regression.

This article has been published from the source link without modifications to the text. Only the headline has been changed.

Source link