This is a web application that classifies iris flowers based on their sepal length, sepal width, petal length, and petal width. The app is built using Streamlit and the classification model is trained using Jupyter notebook.
Python 3.6+
Streamlit
Scikit-learn
Pandas
Numpy
The classification model is trained on the Iris dataset, which is a popular dataset for classification tasks. The dataset contains 150 samples with 3 classes of iris flowers (50 samples for each class).
The classification model is a simple logistic regression model, trained on the Iris dataset. The model achieves an accuracy of 97.8% on the test set.
The Iris dataset is taken from the UCI Machine Learning Repository.