AIF-C01 · Question #345
A company is developing an ML model to predict heart disease risk. The model uses patient data, such as age, cholesterol, blood pressure, smoking status, and exercise habits. The dataset includes a…
The correct answer is B. Supervised learning. Supervised learning is used when the dataset includes both input features (like age, cholesterol, blood pressure, etc.) and a target value indicating the presence of heart disease. The model learns to predict the target value from labeled examples.
Question
A company is developing an ML model to predict heart disease risk. The model uses patient data, such as age, cholesterol, blood pressure, smoking status, and exercise habits. The dataset includes a target value that indicates whether a patient has heart disease. Which ML technique will meet these requirements?
Options
- AUnsupervised learning
- BSupervised learning
- CReinforcement learning
- DSemi-supervised learning
How the community answered
(37 responses)- A11% (4)
- B81% (30)
- C3% (1)
- D5% (2)
Explanation
Supervised learning is used when the dataset includes both input features (like age, cholesterol, blood pressure, etc.) and a target value indicating the presence of heart disease. The model learns to predict the target value from labeled examples.
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