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Question 28

What is the main criteria for separating training and test data when training a machine learning system?

Test data should be as random as possible, so that it tests the boundaries of the system.

Training data should be random, but the test data should be created by a subject matter expert.

Training data should be as random as possible, in order to create a robust model.

The data set should be representative and randomly split in to a training set and a test set so that they do not overlap.

Correct Answer: D

The main criteria for separating training and test data in training a machine learning system is to ensure that the data set is representative and randomly split into a training set and a test set so that they do not overlap. This ensures that the model is trained on a diverse set of data and is tested on data it has not seen before, providing a more accurate evaluation of its performance.

Discussion

CERTIFICATION1990Option: D

D. The data set should be representative and randomly split in to a training set and a test set so that they do not overlap.