Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
A lower loss value indicates better model performance.
B
Loss functions are irrelevant to the choice of classification metrics.
C
The choice of loss function can influence the model's ability to classify different classes correctly.
D
Classification metrics like accuracy only account for true positive cases.
E
Different loss functions can be suited for different classification tasks.
Understanding the Answer
Let's break down why this is correct
Answer
Loss functions are used during training to tell the model how far its predictions are from the true labels; common ones for classification include cross‑entropy for probabilistic outputs and hinge loss for support‑vector machines. After training, evaluation metrics such as accuracy, precision, recall, F1‑score, and ROC‑AUC describe how well the model performs on unseen data. Accuracy counts how many predictions are correct, while precision and recall break down correctness for each class, and F1 balances them. For example, if a model predicts “spam” correctly 80 % of the time but misses many spam emails, its precision may be high but recall low, showing the need to consider multiple metrics. Thus, loss functions guide learning, whereas classification metrics assess final performance.
Detailed Explanation
Loss measures how far predictions are from the true labels. Other options are incorrect because Some think the loss function has no effect on metrics, but it shapes how the model learns; The idea that loss choice does not affect class performance is wrong.
Key Concepts
Loss Functions
Classification Metrics
Model Performance
Topic
Classification Summary
Difficulty
easy level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1Which of the following statements accurately describe loss functions in machine learning? Select all that apply.
easyComputer-science
Practice
2
Question 2Which of the following best describes the role of loss functions in predictive modeling?
easyComputer-science
Practice
3
Question 3Which of the following statements about regularizers in predictive models are correct? Select all that apply.
easyComputer-science
Practice
4
Question 4Which of the following loss functions are suitable for evaluating the performance of multi-class classification models? Select all that apply.
mediumComputer-science
Practice
5
Question 5Loss Function:A :: Classification Metric:?
mediumComputer-science
Practice
6
Question 6When selecting a loss function for a multi-class classification problem, which of the following considerations is most critical for aligning model performance with classification objectives?
mediumComputer-science
Practice
Ready to Master More Topics?
Join thousands of students using Seekh's interactive learning platform to excel in their studies with personalized practice and detailed explanations.