Lesson 3: Classification, Time Series, and Predictive Workflows
Lesson Overview
Develop practical capability in classification, time series, and predictive workflows as part of the MATLAB for Data Analysis and Predictive Modeling learning path.
Topics Covered
Binary and multiclass classification
Trees, nearest neighbors, SVMs, and ensembles
Class imbalance and threshold decisions
Time-series features and forecasting concepts
Train-test and rolling validation patterns
Model comparison
Practical Activity
Build a guided MATLAB exercise covering binary and multiclass classification.
Apply trees, nearest neighbors, svms, and ensembles to a practical engineering or data scenario.
Validate results and troubleshoot an issue involving model comparison.
Key Takeaways
Explain and apply binary and multiclass classification.
Use class imbalance and threshold decisions in a structured workflow.
Validate outputs with plots, metrics, tests, or simulation evidence.
