Streamlit application to compare efficiencies of Machine Learning models in Python

By Rimjhim Singh

This is a streamlit application which is written in Python. The program feeds a dataset (crop dataset) and runs 4 machine learning models on it i.e.: 1. KNN 2. SVM 3. Random forest 4. Naive bayes

This is a streamlit application that is written in Python. The program feeds a dataset (crop dataset) and runs 4 machine learning models on it i.e.:
1. KNN
2. SVM
3. Random forest
4. Naive bayes

All the different models use various parameters that determine their respective accuracies and effciency on a dataset. For each of the model, we can change the values of the parameters using the slider available. The streamlit application shows the shape of the dataset and outputs various graphs as well. The accuracies of all the 4 models are displayed and can be used to determine which one works best for a given dataset. 

You can watch a demonstration video by clicking on the following link. demo video