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Decision Tree Project Overview by ahersuraj23march is a document available to read on EtoBox.

This project explores Decision Trees, a popular machine learning algorithm for classification and regression tasks, detailing their structure, applications, and performance analysis on a dataset. It aims to build and evaluate a Decision Tree model using Python and Scikit-learn while discussing real-world applications, challenges, and future trends. Despite limitations such as overfitting, Decision Trees remain a fundamental tool in machine learning with a reported accuracy of 95.56% in the study.

Author
ahersuraj23march
Language
EN