Machine Learning Practice
A decision tree’s maximum depth changes how finely it divides the data
A decision tree’s maximum depth limits its layers of questions. Compare shallow and deeper trees using held-out data rather than training fit alone.
AI · VISION · EVERYDAY SYSTEMS
Machine Learning Practice
Machine Learning Practice
MAE and RMSE Put Different Weight on Large Prediction Errors
Compare MAE and RMSE with a small prediction-error example, then choose evaluation metrics that reflect the cost of large mistakes in your application.
Machine Learning Practice
Stratified Sampling Preserves Labels, Not Every Important Difference
Stratification can preserve class proportions in a train-test split. It does not automatically balance every feature or prevent data leakage.
Machine Learning Practice
Macro and Micro Averages Can Tell Different Stories About an AI Classifier
Macro and micro averaging answer different questions about classifier performance. Use a small example to see why class balance matters.