Lab

Decision Tree Builder

ID3 Algorithm — Class 11

Dataset

Settings

Training Data

Select a dataset and click Train Tree

Classify New Sample

Train the tree first to classify new samples.

Tree Stats

No tree built yet.

CBSE Concepts

Decision Tree is a supervised classification algorithm. Each internal node tests a feature, branches represent outcomes, and leaves give the class label.

Entropy measures impurity: H = -Σ p·log₂(p). Pure node = 0 entropy.

Information Gain = Entropy(parent) − weighted Entropy(children). We split on the feature with highest gain.