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AI-900: Model Training: Importance of Random Data Split for Better AI Performance

Understand the significance of random data splitting in model training. Discover how splitting data subsets improves AI model accuracy and performance for real-world predictions.

Table of Contents

Question

When training a model, why should you randomly split the rows into separate subsets?

A. to train the model twice to attain better accuracy
B. to train multiple models simultaneously to attain better performance
C. to test the model by using data that was not used to train the model

Answer

C. to test the model by using data that was not used to train the model

Explanation

Randomly splitting rows into separate subsets during model training serves the purpose of option C: to test the model using data that wasn’t part of its training set. This process, commonly known as train-test splitting, helps evaluate how well the model generalizes to new, unseen data. By using a portion of the data for training and keeping another portion aside for testing, it ensures the model isn’t simply memorizing the training data but is learning underlying patterns that apply beyond that specific dataset. This validation with unseen data helps gauge the model’s performance, assessing its ability to make accurate predictions on new information, which is crucial for real-world applicability.

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.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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