Decision Tree and Random Forest


Can anyone explain and help me to understand why decision tree and random forest are Non-linear models ?


A linear model is one which can be expressed using a linear equation (makes sense, right?).

On the other hand a decision tree cannot be expressed using an equation. DTree is more like a flow, based of the condition (ex.: Rain=Yes or No) the tree progresses until a leaf node is reached. This traversing might not be linear hence, non linear model.

Hope this helps.


Thank you Nishant for the detailed explanation. It helped.


One way to look at it is that a condition for a split in a decision tree can be something like “x>3”. This is not a linear condition since 3.0000000000001 is true but 3 is not…


You can read these following links random-forest-and-gradient-boosting-machines


thank you Swapansh for the links