Microsoft AI-100 Designing and Implementing an Azure AI Solution 12 31Oct2024 - Practice Quiz

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Question 1 of 30

A data scientist is tasked with optimizing a machine learning model that predicts customer churn for a subscription-based service. The model currently has an accuracy of 75%, but the business goal is to achieve at least 85% accuracy. The data scientist decides to implement hyperparameter tuning and feature selection techniques. After several iterations, they find that adjusting the learning rate and the number of trees in a gradient boosting model significantly improves performance. Which of the following strategies would most effectively enhance the model\'s predictive accuracy while avoiding overfitting?

Implementing cross-validation during hyperparameter tuning to ensure the model generalizes well to unseen data.

Increasing the complexity of the model by adding more features without assessing their relevance.

Reducing the training dataset size to speed up the training process.

Using a single validation set to tune hyperparameters without any form of resampling.

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