Clarifying the requirement for a satisficing metric in model evaluation
Question: According to the source text, what does it mean to set a criterion, such as a model's running time or binary file size, as a satisficing metric?
Sample answer: Setting a criterion as a satisficing metric means that you simply require it to meet a certain threshold or acceptable value, rather than trying to maximize or minimize it.
Key points:
- Satisficing metrics simply require meeting a certain threshold value.
- They are not optimized or maximized; they only act as acceptable limits.
Rubric: To earn full credit, the answer must explain that a satisficing metric only requires the model to meet a certain specified threshold value rather than being optimized or maximized.
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Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
Machine Learning Yearning @ DeepLearning.AI
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Defining satisficing and optimizing metrics for a mobile machine learning application
Clarifying the requirement for a satisficing metric in model evaluation