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Mushroom-Classification-using-Streamlit

A typical Classification Machine Learning project leverages mushrooms data to classify them as edible or poisonous. This web app is aimed to train any model given by the user and also the user can vary the parameters and see the results accordingly to see which model and parameters fit accurately.

This project tries to create a model based on data provided at https://www.kaggle.com/uciml/mushroom-classification. The output algorithms have been used to test if they can maintain their accuracy in classifying the mushrooms . As this is a problem of binary classification; Three algorithms have been used:

  1. Support Vector Machine Classifier.
  2. Logistic Regression.
  3. Random Forest Classifier.

This project is licensed under the MIT LICENSE.

Web App Link

https://mush-class.herokuapp.com

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Machine Learning Classification Web App built using Streamlit and deployed on heroku platform.

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