Which ONE of the following combinations of Training, Validation, Testing data is used during the process of learning/creating the model? SELECT ONE…

The process of developing a machine learning model typically involves the use of three types of

datasets:

Training Data: This is used to train the model, i.e., to learn the patterns and relationships in the data.

Validation Data: This is used to tune the model’s hyperparameters and to prevent overfitting during

the training process.

Test Data: This is used to evaluate the final model’s performance and to estimate how it will perform

on unseen data.

Let's analyze each option:

A . Training data - validation data - test data

This option correctly includes all three types of datasets used in the process of creating and

validating a model. The training data is used for learning, validation data for tuning, and test data for

final evaluation.

B . Training data - validation data

This option misses the test data, which is crucial for evaluating the model’s performance on unseen

data after the training and validation phases.

C . Training data - test data

This option misses the validation data, which is important for tuning the model and preventing

overfitting during training.

D . Validation data - test data

This option misses the training data, which is essential for the initial learning phase of the model.

Therefore, the correct answer is A because it includes all necessary datasets used during the process

of learning and creating the model: training, validation, and test data​​.