Practice Advanced Evaluation Techniques - 12.5 | 12. Model Evaluation and Validation | Data Science Advance
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Advanced Evaluation Techniques

12.5 - Advanced Evaluation Techniques

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is bootstrapping?

💡 Hint: Think about how we estimate variability in statistics.

Question 2 Easy

What does a confusion matrix display?

💡 Hint: Consider the four possible outcomes of a classification task.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is bootstrapping primarily used for?

Data Preprocessing
Model Evaluation
Feature Selection

💡 Hint: Think about the purpose of resampling.

Question 2

True or False: Time-series cross-validation allows using future information when training a model.

True
False

💡 Hint: Consider the implications of causal relationships in time series.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

💡 Hint: What changes would you make to your dataset?

Challenge 2 Hard

Given a confusion matrix showing a high rate of false positives, suggest model tuning strategies to address this issue.

💡 Hint: What impact does changing the threshold have on classification outcomes?

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