Iris Flower Classification

[greeshma275]

The Iris Flower Classification project involves developing a machine learning model to classify iris flowers into three species: Setosa, Versicolor, and Virginica. Using the widely recognized Iris dataset, which contains features such as sepal length, sepal width, petal length, and petal width, we employ algorithms like Random Forest to build the classification model. The project demonstrates data preprocessing techniques, including feature scaling and train-test splitting, followed by training the model and making predictions. Evaluation metrics such as accuracy, confusion matrix, and classification report help assess the model's performance.

[github-actions]

Thanks for creating the issue in ML-Nexus!🎉
Before you start working on your PR, please make sure to:

• ⭐ Star the repository if you haven't already.
• Pull the latest changes to avoid any merge conflicts.
• Attach before & after screenshots in your PR for clarity.
• Include the issue number in your PR description for better tracking.
  Don't forget to follow @UppuluriKalyani – Project Admin – for more updates!
  Tag @Neilblaze,@SaiNivedh26 for assigning the issue to you.
  Happy open-source contributing!☺️

[greeshma275]

Please assign Level

[github-actions]

Hello @greeshma275! Your issue #705 has been closed. Thank you for your contribution!