An interactive Web Application using streamlit library was implemented to analyse and classify the mushroom dataset. The application was made by training Logistic Regression, Random Forest, and Support Vector Classifiers using scikit-learn and later the results were plotted to evaluate metrics for binary classification algorithms.
Task 1: Load Terminal and run commands mentioned below
Task 2: Load the Mushrooms Data Set
Task 3: Creating Training and Test Sets
Task 4: Plot Evaluation Metrics
Task 5: Training a Support Vector Classifier
Task 6: Training a Support Vector Classifier
Task 7: Train a Logistic Regression Classifier
Task 8: Training a Random Forest Classifier
In anaconda prompt
1- Traverse through to the stored file using cd
2- code app.py (python file name)
3- Run the streamlit library by using : streamlit run app.py(py file name)