The aim of this project is to print steps for every split in the decision tree from scratch and implementing the actual tree using sklearn. Iris dataset has been used, the continuous data is changed to labelled data. In this code gain ratio is used as the deciding feature to split upon.
A simple implementation of the ID3 algorithm in Rust.
Machine learning classifiers project focused on building models from scratch/with libraries and evaluating performance using standard metrics (accuracy/precision/recall), proper data splitting, and clean experiment structure. Emphasis on correctness, numerical stability.
implemented decision tree using metrics (Gain ratio)
repo for the python implementation of decision tree with rule post pruning
Add a description, image, and links to the gain-ratio topic page so that developers can more easily learn about it.
To associate your repository with the gain-ratio topic, visit your repo's landing page and select "manage topics."