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Exercise 2: Plot Evaluation Metrics using Streamlit

Explore how to visualize key classification evaluation metrics including confusion matrix, ROC curve, and precision-recall curve using Streamlit. This lesson guides you to implement interactive plots for machine learning model assessment within a Python web application.

Evaluation metrics

You must plot the following evaluation metrics for all the models on the breast cancer dataset.

  • Confusion Matrix
  • Receiving Operating Characteristic (ROC) Curve
  • Precision-Recall Curve

Task 1

Write the Python code to add multiselect option on the left sidebar as shown in the figure below:

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