https://j-zohdi.herokuapp.com/svm_visualizer
This project creates visualizations and provides a web API for a list of support vector machine models. This gives easy access as a tool for analyzing data with visual output. That can be used by anyone with internet access, anywhere, with any skillset. Just input your data and sit back.
The models included are implemented by the python library sci-kit learn.:
- Linear
- Polynomial
- Radial Basis Function
- Logistic Regression
- K-Nearest Neighbors
- Decision Tree
- Random Forest
Web API is written in Flask Charts by Plotly2 Hosted on Heroku
The intended use is as a web app. But you can install and run locally as long as you set up a mongo database. The reason for doing this is that the models may take quite some time to compute the result, depending out the input. My solution to providing an API is to send back an ID to the initial request. This ID will then be used to poll the result from the database which will be uploaded once the model is finished computing.
Project is under MIT License