Which AI data management technique involves creating validation and test data?

The correct answer is B. Splitting. Data splitting is the technique of partitioning a dataset into distinct subsets-commonly training, validation, and test sets. The training set teaches the model, the validation set is used for hyperparameter tuning and early stopping, and the test set provides an unbiased final…

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Question

Options

ALearning
BSplitting
CTraining
DAnnotating

How the community answered

(41 responses)

A
2% (1)
B
93% (38)
C
5% (2)

Explanation

Data splitting is the technique of partitioning a dataset into distinct subsets-commonly training, validation, and test sets. The training set teaches the model, the validation set is used for hyperparameter tuning and early stopping, and the test set provides an unbiased final evaluation. This is the specific process that 'creates' validation and test data from raw data. Annotating involves labeling data, training is the model-learning phase, and learning is a broader concept describing the model's optimization process-none of these specifically produce the split subsets.

Topics

#Data Splitting#Validation Data#Test Data#AI Data Management

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