# DecisionTreeGenerator

**Repository Path**: ABCpril/DecisionTreeGenerator

## Basic Information

- **Project Name**: DecisionTreeGenerator
- **Description**: Generates and visualizes a decision tree model using a training data set by using the ID3 algorithm. Able to test accuracy of the model using test data set. Pruning and gain ratio feature included.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-10-13
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DecisionTreeGenerator

**This application can develop a decision tree from a training data set containing categorical attributes and a class label. In the example below, Outlook, Temperature, Humidity, and Wind are the categorical attributes (inputs). PlayTennis is the class label (output).
The objective is to create a decision tree so we can make predictions on what the class label (output) will be, given a set of categorical attribute values (inputs)**

![](images/playTennis_dataset.PNG)

**The decision tree below was modeled using the ID3 algorithm.**

![](images/playTennis_tree.PNG)