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Sensitivity of Predictors
easy

A new predictor model is being developed. If the model shows significant changes in its predictions with slight variations in the input data, how would you classify its sensitivity?

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Learning Path

Question & Answer
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Choose AnswerChoose the Best Answer

A

Highly Sensitive

B

Insensitive

C

Moderately Sensitive

D

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
Predictor Stability
Empirical Risk Minimization
Topic

Sensitivity of Predictors

Difficulty

easy level question

Cognitive Level

understand

Deep Dive: Sensitivity of Predictors

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Definition
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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