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Loss Functions
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Mean Squared Error : Predictive Accuracy :: Cross-Entropy : ?

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Learning Path

Question & Answer
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Choose AnswerChoose the Best Answer

A

Model Complexity

B

Classification Performance

C

Overfitting Risk

D

Feature Importance

Understanding the Answer

Let's break down why this is correct

Cross‑entropy measures how well a model predicts the right class. Other options are incorrect because Loss functions do not tell how many parameters a model has; A low loss does not automatically mean the model is overfitting.

Key Concepts

Loss Functions
Predictive Performance
Classification
Topic

Loss Functions

Difficulty

medium level question

Cognitive Level

understand

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Definition
Definition

Loss functions quantify how well a predictor approximates the true output values. They are used to measure the discrepancy between predicted and actual values. Common examples include quadratic loss functions that penalize the squared differences.

Topic Definition

Loss functions quantify how well a predictor approximates the true output values. They are used to measure the discrepancy between predicted and actual values. Common examples include quadratic loss functions that penalize the squared differences.

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