A decision tree is a flowchart that starts with one main idea and then branches out based on the consequences of your decisions. The model is a form of supervised learning, meaning that the model is trained and tested on a set of data that contains the desired categorization.
This project is based in the ID3 algorithm.
ID3 stands for Iterative Dichotomiser 3 and is named such because the algorithm iteratively (repeatedly) dichotomizes(divides) features into two or more groups at each step.
It was invented by Ross Quinlan, ID3 uses a top-down greedy approach to build a decision tree.
Dataset: Tennis dataset is chosen. There are 4 attributes: Outlook, Temp, Humidity, Wind. The final output will be whether a game will be played or not based on the conditions.