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1
Explain your notebook/project.
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2
How did you handle outliers?
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3
Is removing outliers always a good practice?
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4
What can you do instead of removing outliers?
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5
What is collinearity?
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6
If two features are highly correlated, what should you do?
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7
Explain Bagging.
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8
Explain Boosting.
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9
How does Bagging work?
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10
How does Boosting work?
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11
Explain Decision Tree.
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12
How does a Decision Tree work?
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13
What is Entropy?
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14
Why are Bagging and Boosting better than a single Decision Tree?
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15
What are different evaluation metrics?
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16
Write the formulas for evaluation metrics.
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17
Why is Accuracy not always a good evaluation metric?
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18
For a diabetes dataset, which evaluation metric would you choose and why?
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19
How does Logistic Regression work?
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20
How does KNN work?