The Instance-Based Learning Quiz: Are You an Expert?

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| By Madhurima Kashyap
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Madhurima Kashyap
Community Contributor
Quizzes Created: 39 | Total Attempts: 11,612
| Attempts: 84
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  • 1/10 Questions

    What is instance-based learning?

    • Learning based on general rules
    • Learning based on specific instances
    • A type of reinforcement learning
    • A type of unsupervised learning
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About This Quiz

The Instance-Based Learning Quiz: Are You an Expert?" is a meticulously crafted questionnaire that evaluates your knowledge about instance-based learning. Instance-Based Learning Quiz delves into the fundamental nature of instance-based learning, standard algorithms such as K-Nearest Neighbors (KNN), and how it works.
It helps assess your understanding of key advantages and disadvantages, particularly computational costs and the absence of a training phase. The quiz further scrutinizes your grasp on elements like 'K' in KNN, decision-making processes, distance metrics, and decision boundaries' behavior with varying 'K' values. Concluding with real-world applications of KNN, this quiz presents a comprehensive check on your proficiency in instance-based learning.

The Instance-based Learning Quiz: Are You An Expert? - Quiz

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  • 2. 

    Which of the following is a type of instance-based learning?

    • Regression

    • Classification

    • Clustering

    • K-Nearest Neighbors (KNN)

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  • 3. 

    Which algorithm is commonly used in instance-based learning?

    • Decision Trees

    • Support Vector Machines

    • K-Nearest Neighbors (KNN)

    • None of the above

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  • 4. 

    What is the main disadvantage of instance-based learning?

    • It has high computational cost.

    • It requires a training phase.

    • It is resistant to noisy data.

    • All of the above

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  • 5. 

    In the context of instance-based learning, what is K in K-Nearest Neighbors (KNN)?

    • The type of distance metric used

    • The number of clusters

    • The number of nearest neighbors

    • The type of classification task

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  • 6. 

    How does K-Nearest Neighbors (KNN) make predictions?

    • By finding the nearest cluster

    • By finding the nearest K instances

    • By finding the nearest rule

    • By finding the nearest hyperplane

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  • 7. 

    Which of the following is a real-world application of K-Nearest Neighbors (KNN)?

    • Image Recognition

    • Speech Recognition

    • Recommender Systems

    • All of the above

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  • 8. 

    What is the main advantage of instance-based learning?

    • It has low computational cost.

    • It doesn't require a training phase.

    • It is resistant to noisy data.

    • All of the above

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  • 9. 

    Which distance metric is commonly used in K-Nearest Neighbors (KNN)?

    • Euclidean distance

    • Manhattan distance

    • Cosine distance

    • All of the above

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  • 10. 

    In K-Nearest Neighbors (KNN), how does changing the value of K affect the decision boundary?

    • Larger K makes the decision boundary smoother

    • Smaller K makes the decision boundary smoother

    • K does not affect the decision boundary

    • None of the above

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Quiz Review Timeline (Updated): Aug 3, 2023 +

Our quizzes are rigorously reviewed, monitored and continuously updated by our expert board to maintain accuracy, relevance, and timeliness.

  • Current Version
  • Aug 03, 2023
    Quiz Edited by
    ProProfs Editorial Team
  • Aug 02, 2023
    Quiz Created by
    Madhurima Kashyap
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