Question: Subject: Machine Learning Question Number 1: A dataset showing the decisions about presence of Heart Disease (HD) based on four attributes (Age, Blood pressure, Cholesterol
Subject: Machine Learning
Question Number 1:
A dataset showing the decisions about presence of Heart Disease (HD) based on four attributes (Age, Blood pressure, Cholesterol and Heart rate) is listed in the following table:
| Age | BP | CH | HR | HD |
| Old | Low | Low | Medium | No |
| Very old | Low | Medium | Low | Yes |
| Old | Medium | Medium | Medium | No |
| Old | Low | Low | Low | Yes |
| Mild | Low | Low | Medium | Yes |
| Very old | High | Medium | Low | Yes |
| Very old | Medium | Medium | Low | Yes |
| Mild | Medium | Very high | Low | Yes |
| Old | Low | Medium | Medium | No |
| Very old | Medium | Very high | Medium | No |
| Very old | Medium | Low | Medium | No |
| Mild | Low | Medium | Medium | No |
| Mild | Low | Medium | Medium | No |
- Compute the entropy for this data set.
- What is the information gain for the Heart Rate (HR) feature?
- Given a choice among Age, Blood pressure, Cholesterol and Heart rate, which feature would the ID3 algorithm choose as the root node for a decision tree.
- What is the role of information gain and entropy in ID3 algorithm?
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