Active Learning Principles
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What is the fundamental difference between active learning and passive learning?

  • Active learning involves a one-way flow of information, while passive learning involves a multi-directional flow.
  • Active learning guarantees the flow of information in many directions, while passive learning involves a unidirectional flow. (correct)
  • Active learning requires human involvement, while passive learning is fully automated.
  • Active learning is a concept originated from educational literature, while passive learning is a machine learning concept.

    • What is the primary objective of the problem formulation described in the text?

  • To represent the 'irregularity' measure of a fruit using a single real-valued input feature.
  • To estimate the parameterized threshold $\theta$ from a set of labeled data using supervised learning.
  • To develop a classifier that can distinguish between safe and noxious fruits based on their shape. (correct)
  • To determine the optimal number of training data points required for achieving 99% accuracy.

    • Which of the following statements best describes the assumption made in the problem formulation?

  • The output classification is binary, with fruits being either safe or noxious, based on their shape.
  • The supervised learning model assumes that the training data is labeled with the correct classifications of safe and noxious fruits.
  • The input feature $x$ represents the 'irregularity' measure of the fruit's shape, which is assumed to be a real-valued quantity. (correct)
  • The input feature $x$ represents the fruit's color, which is assumed to be a real-valued measure of its safety.

    • How is the classifier function defined?

    <p>The classifier is a function that maps the input feature $x$ to a binary output {safe, noxious} using a threshold $\theta$.</p> Signup and view all the answers

    Based on the information provided, what technique is suggested for obtaining the best classifier model?

    <p>Supervised learning, where the model estimates the parameterized $\theta$ from a set of labeled training data.</p> Signup and view all the answers

    What is the ultimate goal or question being addressed?

    <p>How many training data points are required to achieve a 99% accurate classifier for distinguishing safe and noxious fruits.</p> Signup and view all the answers

    Which of the following statements is NOT true according to the information provided in the text?

    <p>The objective is to develop a classifier that can distinguish between safe and noxious fruits based on their color.</p> Signup and view all the answers

    What is the significance of the term 'active learning' in the context of this text?

    <p>It describes the multi-directional flow of information involved in the learning process, as opposed to passive learning.</p> Signup and view all the answers

    Which of the following statements best describes the relationship between active learning and the problem formulation described in the text?

    <p>The problem formulation is not directly related to active learning, as it focuses on supervised learning techniques.</p> Signup and view all the answers

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