3 - Train/Test Split
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Practice Questions
Test your understanding with targeted questions
What is the purpose of the Train/Test Split?
💡 Hint: Think about why testing on unseen data is necessary.
What can you infer if your model performs well on the training set but poorly on the test set?
💡 Hint: Consider model bias and prediction generalization.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary goal of a Train/Test Split?
💡 Hint: Consider what the primary function of separating data into two parts is.
True or False: The 'random_state' parameter ensures reproducibility of the Train/Test Split.
💡 Hint: Think about why reproducing results are important in data science.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Consider a dataset of 10,000 samples. If you want to perform an 80/20 train/test split, how many samples would be used for training and testing?
💡 Hint: Calculate 20% of the total samples for testing.
In a scenario where your model performs excellently on the training data yet poorly on test data, what potential issues could cause this discrepancy? Discuss and suggest solutions.
💡 Hint: Think about the relationship between training data, model complexity, and generalization.
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