Learn how to answer a question about validation set in the AI-900 exam. Understand the difference between training, validation, and test sets, and how to use them to evaluate and improve a machine learning model.
Table of Contents
Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Statement 1: A validation set includes the set of input examples that will be used to train a mode.
Statement 2: A validation set can be used to determine how well a model predicts labels.
Statement 3: A validation set can be used to verify that all the training data was used to train the model.
Answer
Statement 1: A validation set includes the set of input examples that will be used to train a mode: No
Statement 2: A validation set can be used to determine how well a model predicts labels: Yes
Statement 3: A validation set can be used to verify that all the training data was used to train the model: No
Explanation
Statement 1: No. A validation set is a subset of the data that is not used to train the model, but is used to evaluate the model’s performance and tune its hyperparameters.
Statement 2: Yes. A validation set can be used to determine how well a model predicts labels by comparing the predicted labels with the actual labels in the validation set. This can help measure the model’s accuracy, precision, recall, and other metrics.
Statement 3: No. A validation set cannot be used to verify that all the training data was used to train the model. A validation set is separate from the training data, and is not used to update the model’s weights or biases. To verify that all the training data was used to train the model, one can use a training log or a confusion matrix.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.
