Decision Tree Classifier Practical Implementation

This project demonstrates the implementation of a Decision Tree Classifier using the Iris dataset from Scikit-learn.

Project Overview

In this project, I practiced:

• Decision Tree Classification
• Train-Test Split
• Model Training
• Accuracy Evaluation
• Confusion Matrix
• Classification Report
• Decision Tree Visualization
• Pre-pruning
• Hyperparameter Tuning using GridSearchCV

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Dataset Used

• Iris Dataset from Scikit-learn
• Total samples: 150
• Features:
  • Sepal Length
  • Sepal Width
  • Petal Length
  • Petal Width

Target Classes:

• Setosa
• Versicolor
• Virginica

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Libraries Used

• pandas
• numpy
• matplotlib
• scikit-learn

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Model Used

DecisionTreeClassifier()