Deep Learning Algorithms: Memorization vs Modeling
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Questions and Answers

What is the primary goal of a classification machine learning model?

  • To predict a continuous output
  • To split the given training data into two or more classes (correct)
  • To maximize the uncertainty of the output
  • To minimize the error between predicted and actual output

What determines the specific decision boundary in a classification model?

  • The type of classification algorithm used
  • The value of the parameters w (correct)
  • The number of input features
  • The size of the training dataset

What type of learning is involved in classification?

  • Unsupervised learning
  • Semi-supervised learning
  • Supervised learning (correct)
  • Reinforcement learning

In the example of the medical problem, what is the purpose of the classification model?

<p>To determine the likelihood of a voice pathology (B)</p> Signup and view all the answers

What is the role of the decision boundary in a classification model?

<p>To separate the input data into distinct classes (B)</p> Signup and view all the answers

What is the output of a classification model in the example of the medical problem?

<p>A discrete value of +1 or -1 (A)</p> Signup and view all the answers

What is the primary goal of classification in machine learning?

<p>Minimizing the misclassification error on the training data (B)</p> Signup and view all the answers

Why do complex classifiers often perform poorly on test data?

<p>Due to the effect of randomness in the real-world data (B)</p> Signup and view all the answers

What is the characteristic of linear classification models?

<p>They are very simple and nearly all modeling with little to no memorization (A)</p> Signup and view all the answers

What is the trade-off between model complexity and test error?

<p>As model complexity increases, test error increases (C)</p> Signup and view all the answers

What is the preferred approach to model selection?

<p>Selecting the simplest model that is evidenced by the data (C)</p> Signup and view all the answers

Why are linear models often too simple in practice for most real-world machine learning applications?

<p>Because they are not capable of handling complex relationships (D)</p> Signup and view all the answers

What is the main issue with storing all possible images in a database?

<p>There is no database in the universe large enough to store them. (C)</p> Signup and view all the answers

What is the term used in medical terms for the activity of capturing images of all possible images?

<p>Triage (B)</p> Signup and view all the answers

What is the goal of a classification model in medical triage?

<p>To find the best parameters to split the feature space into two regions. (B)</p> Signup and view all the answers

What is the purpose of the classification boundary in a classification model?

<p>To split the feature space into two regions. (D)</p> Signup and view all the answers

Why are supervised machine learning models imperfect?

<p>Because they cannot solve all possible input-output pairs. (A)</p> Signup and view all the answers

What is the conclusion about machine learning based on its limitations?

<p>Machine learning is more than just memorization, it requires careful modeling. (A)</p> Signup and view all the answers
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