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5 votes
Which of the following is NOT a correct partition?

A. Training partition
B. Validation partition
C. Cross-validation
D. Test partition

1 Answer

3 votes

Final answer:

Cross-validation is not a correct partition in the context of data analysis and machine learning.

Step-by-step explanation:

Out of the given options, Cross-validation is not a correct partition in the context of data analysis and machine learning.

A training partition is used to train a model by providing it with labeled data.

A validation partition is used to fine-tune the model's hyperparameters and assess its performance on unseen data.

A test partition is used to evaluate the final performance of the model on independent data.

Cross-validation is a technique used to estimate the model's performance by repeatedly partitioning the data into training and validation sets.

User James Harrington
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