Decision Tree
what is it?
A decision tree is a simple way to make choices in machine learning. It’s like a tree with branches. Each branch asks a question about your data, like "Is it a school day?" or "Is it cold?" The tree splits data into groups until it gives an answer, like "Wear a jacket" or "Wear a t-shirt." Decision trees are easy to understand and can be shown as a picture. They work for sorting things (like true/false) or guessing numbers.
classifier or regressor?
It is better to use it as a classifier. regressor usually is not enough powerfull as its counterpart.
a usefull guide
if the tree gets too big, it might not work well with new data. Keeping the tree small helps fix this. People like decision trees because they’re clear and work with all kinds of data.
better algorythme?
XGBOOST is the updated decision tree. you can read it here link
