Tree based methods in ML

Inspiration

Machine learning has always been something I am intrigued by and I thought implementing Decision tree and Random forest algorithms in python would be interesting.

What it does

On a given dataset, the decision tree and random forest algorithms (scratch code + using built-in functions) are run and the accuracies can be compared at the end.

How we built it

Challenges we ran into

Writing the scratch code was definitely difficult but with the help of different tutorials and videos, I managed to write it.

What we learned

Learned more about tree based methods and how they are implemented in ML.

Built With

• jupyter
• python