Machine Learning

Logistic Regression

A linear model that outputs a probability. The baseline every classification project should start from.

Despite the name it is a classifier: a linear combination of features squashed through a sigmoid into a probability between zero and one.

Its value is that each coefficient means something you can say out loud, it trains in seconds, and it is well calibrated by default. If a complex model cannot beat it by a margin worth the extra risk, it should not ship.

Also in Machine Learning

Supervised Learning Unsupervised Learning K-Means K-Nearest Neighbours Linear Regression PCA

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