Learning Path
Question & Answer
Choose the Best Answer
Highly Sensitive
Insensitive
Moderately Sensitive
Stable
Understanding the Answer
Let's break down why this is correct
When tiny tweaks in the input make the output jump a lot, the model is reacting strongly. Other options are incorrect because People might think a model that changes a lot is not sensitive, but that is wrong; Moderately sensitive would mean the model reacts, but not as wildly.
Key Concepts
Sensitivity of Predictors
easy level question
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Deep Dive: Sensitivity of Predictors
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Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
Topic Definition
The sensitivity of a predictor measures its responsiveness to changes in input features. Insensitive predictors exhibit stability in their predictions when inputs are close. Sensitivity is crucial for generalization and performance, especially with limited training data.
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