Practice - Initial Data Split for Final, Unbiased Evaluation (Crucial Step)
Practice Questions
Test your understanding with targeted questions
What is the purpose of performing a train-test split in machine learning?
💡 Hint: Think about the differences between seen and unseen data.
What is the typical ratio of training to testing data?
💡 Hint: This is a common practice in many machine learning tasks.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What do we aim to achieve by performing an initial data split?
💡 Hint: Consider the role of unseen data in validating your model.
True or False: A model can generalize well if it is only trained on the entire dataset without a test set.
💡 Hint: Think about the generalization of the trained model.
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Challenge Problems
Push your limits with advanced challenges
Create a report explaining how you would ensure the reliability of your model’s performance using a test set, including specific metrics you would collect.
💡 Hint: Think about the metrics that best represent the model’s performance.
Describe a modification you would propose for the conventional train-test split method to improve model evaluation reliability.
💡 Hint: Consider how to make sure no group is left out in evaluations.
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Reference links
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