Microsoft PL-600 Microsoft Power Platform Solution Architect 04 31Oct2024 - Practice Quiz

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In a scenario where a company is integrating AI and machine learning into its customer relationship management (CRM) system, they aim to predict customer churn based on historical data. The data includes customer demographics, purchase history, and interaction logs. The team decides to use a supervised learning approach with a logistic regression model. If the model achieves an accuracy of 85% on the training set and 75% on the validation set, what does this indicate about the model\'s performance, and what steps should the team consider next to improve the model?

The model may be overfitting, and the team should consider regularization techniques or gathering more data.

The model is performing well, and no further action is needed.

The model is underfitting, and the team should increase the complexity of the model.

The model's accuracy on the validation set is sufficient, and the team should deploy it immediately.

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