Intelligent Classifier

Intelligent Classifier is a web application that allows you to explore and visualize the impact of different machine learning algorithms on classification tasks. It provides an interactive interface to adjust algorithm parameters and observe decision boundaries, empowering you to make informed decisions in your classification projects.

Features

Random Forest Classifier: Adjust the number of estimators and maximum depth to see how they affect the classification results. Visualize decision boundaries in real-time.
Support Vector Classifier: Explore the impact of the regularization parameter (C) and the kernel coefficient (gamma) on the classification accuracy and decision boundaries.
K-Nearest Neighbors Classifier: Experiment with the number of neighbors and observe the changes in accuracy and decision boundaries.

How to Use

Install the necessary dependencies by running pip install -r requirements.txt in your command line.
Run the application by executing streamlit run app.py in your command line.
Access the application by opening the provided URL in your web browser.
Select a model from the sidebar to explore its parameters.
Adjust the parameters using the sliders and observe the changes in accuracy and decision boundaries.
Explore different models and parameter settings to gain insights into the classification process.