Welcome to the Iris Flower Classification App! This interactive web application leverages the power of machine learning to classify Iris flowers based on user input, specifically using a Random Forest Classifier.
A demo of the app running is available at: https://iris-classification-ui.streamlit.app/
Credits: The project is inspired by https://365datascience.com/blog/authors/santiago-viquez/
This project provides a simple tool for classifying the species of Iris flowers. The app is designed with an intuitive user interface that allows users to enter specific measurements related to an Iris flower's sepal length, sepal width, petal length, and petal width. Based on these inputs, the application predicts the Iris species, identifying it as one of the three known classes:
- Setosa
- Versicolor
- Virginica
The model used for classification is a Random Forest Classifier, a reliable and widely used machine learning algorithm that is well-suited for this type of multi-class classification problem. The classifier has been trained on the classic Iris dataset, known for its simplicity and effectiveness in demonstrating basic classification techniques.
- Input Measurements: Enter the desired values for sepal length, sepal width, petal length, and petal width in the provided slider inputs.
- Get Prediction: Just click Predict class and the app will instantly display the predicted Iris species based on the input measurements.
Happy classifying!