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5 cards from this section. Quick, good the night before a test.
What is bootstrapping?
Think about how we estimate variability in statistics.
What does a confusion matrix display?
Consider the four possible outcomes of a classification task.
What is bootstrapping primarily used for?
Think about the purpose of resampling.
True or False: Time-series cross-validation allows using future information when training a model.
Consider the implications of causal relationships in time series.
A model yields a significant discrepancy in accuracy using standard cross-validation versus time-series validation. Discuss the implications and necessary adjustments in model training.
What changes would you make to your dataset?
Given a confusion matrix showing a high rate of false positives, suggest model tuning strategies to address this issue.
What impact does changing the threshold have on classification outcomes?
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