Classical ML in One Lesson

1. What is the primary function of classical supervised learning models?

To generate text from unstructured data To predict outcomes based on historical data To cluster similar data points together To detect anomalies in real-time data

2. Which model is often considered the simplest and most explainable for predicting numerical outcomes?

Decision trees Linear regression Gaussian mixture models Gradient-boosted trees

3. In which situation is classical machine learning preferred over LLMs according to the lesson?

Summarizing lengthy documents Predicting processing times from features Evaluating text for equivalence Extracting named entities from unstructured text

4. What evaluation metric measures the proportion of actual positive cases that were correctly identified?

Recall Precision Accuracy F1 Score

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