Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
The chosen loss function
B
The size of the dataset
C
The complexity of the model
D
The random initialization of parameters
Understanding the Answer
Let's break down why this is correct
Answer
In Empirical Risk Minimization the model parameters are chosen to minimize the empirical risk, which is the average loss of the model on the training data. The empirical risk directly tells us how well a particular set of parameters fits the observed examples, so the algorithm picks the parameters that make this average loss as small as possible. For example, if we are fitting a linear regression model, the empirical risk is the mean squared error over all training points; the parameters that give the smallest mean squared error are selected. Thus, the empirical risk itself is the factor that most directly determines the parameter choice.
Detailed Explanation
The loss function tells the algorithm how bad a prediction is. Other options are incorrect because Many think a bigger dataset forces the model to pick different parameters; People often think a more complex model automatically changes parameters.
Key Concepts
Empirical Risk Minimization
Loss Function
Model Complexity
Topic
Empirical Risk Minimization
Difficulty
medium level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1In the context of Empirical Risk Minimization, how does overfitting relate to the choice of loss function?
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2
Question 2In the context of Empirical Risk Minimization, which of the following scenarios is most likely to lead to underfitting while impacting the generalization error negatively?
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3
Question 3In the context of Empirical Risk Minimization, how does the choice of a loss function affect the consistency of estimators within a given hypothesis space?
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4
Question 4In the context of Empirical Risk Minimization, the process of selecting parameters that minimize the average loss is often referred to as __________.
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5
Question 5Which of the following statements accurately describe Empirical Risk Minimization (ERM)? Select all that apply.
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6
Question 6Which of the following scenarios best exemplifies the application of Empirical Risk Minimization in model training?
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7
Question 7Empirical Risk Minimization (ERM) : Finding the best model parameters :: Gradient Descent : ?
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