Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
Minimizing the loss function
B
Calculating the average loss
C
Selecting the training dataset
D
Evaluating model performance
Understanding the Answer
Let's break down why this is correct
Answer
Empirical Risk Minimization is the problem of selecting the model parameters that give the lowest average loss on the training data. Gradient Descent is the routine that moves the parameters step by step in the direction that most reduces that loss. At each step it computes the loss gradient, scales it by a learning rate, and subtracts that from the current parameters. For example, if a linear regression model has weight 2, a gradient of 0. 5 and a step size of 0.
Detailed Explanation
ERM chooses parameters by reducing the average loss. Other options are incorrect because The mistake is thinking Gradient Descent only calculates an average; Some think Gradient Descent picks the training data.
Key Concepts
Empirical Risk Minimization
Gradient Descent
Loss Function
Topic
Empirical Risk Minimization
Difficulty
medium level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1A data scientist is tasked with building a predictive model to forecast sales based on historical data. To ensure the model performs well, they decide to apply empirical risk minimization (ERM). Which of the following actions best represents the application of ERM in this scenario?
easyComputer-science
Practice
2
Question 2In the context of Empirical Risk Minimization, the process of selecting parameters that minimize the average loss is often referred to as __________.
hardComputer-science
Practice
3
Question 3Which of the following statements accurately describe Empirical Risk Minimization (ERM)? Select all that apply.
easyComputer-science
Practice
4
Question 4Which of the following scenarios best exemplifies the application of Empirical Risk Minimization in model training?
mediumComputer-science
Practice
5
Question 5In the context of Empirical Risk Minimization, which factor most directly influences the selection of model parameters?
mediumComputer-science
Practice
6
Question 6How does empirical risk minimization (ERM) ensure that a predictive model generalizes well to unseen data?
mediumComputer-science
Practice
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