Statistical Learning: Classification

Date & Time: Thu., Dec. 16, 2021 • 1–3 p.m. CT

Instructor:

• Sutanoy Dasgupta | Texas A&M Statistics | sutanoy@tamu.edu

STATISTICAL LEARNING: CLASSIFICATION

Learning Objectives:

• Identify the appropriate type of machine learning algorithm based on problem description.
• Apply Naive Bayes Classification to Biomedical datasets using R.
• Apply Decision Trees Classification to Biomedical datasets using R.
• Apply Random Forest Method to Biomedical datasets using R.
• Apply K Nearest Neighbors  Classification to Biomedical datasets using R.
• Evaluate the performance of classification methods.

SESSION MATERIALS

The instructor will present using an R notebook that integrates exposition with executable code examples, exercises and quizzes.

You can run your own copy of the notebook in a web browser using Google Colab. No further software installation is required.

To view the notebook: click on the link below

To run notebook code: you must be signed into a Google account and click “run anyway” if prompted.

• View the notebook in Google Colab

Recorded Session:

Post about the program on social media and use this hashtag!
#TAMIDSBiomedicalDataScience