Machine Learning Test

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| By Livyn
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  • 1/10 Questions

    What's the name of the other category?

    • Unsupervised learning
    • Semi-supervised learning
    • Reinforcement learning
    • Active learning
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About This Quiz

Machine learning is a field of computer science that focuses on making machines learn. It's also a revolutionary aspect of the science world and as we're all part of that, I wonder how much you know about it.

Machine Learning Test - Quiz

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  • 2. 
    What happens in clustering? - ProProfs

    What happens in clustering?

    • An exponential of the inputs is found

    • Inputs are multiplied

    • Inputs are divided into groups

    • Sets are multiplied

    Correct Answer
    A. Inputs are divided into groups
    Explanation
    In clustering, the inputs are divided into groups based on their similarities or patterns. This process involves grouping similar data points together and separating them from other dissimilar data points. By dividing the inputs into groups, clustering helps in identifying distinct clusters or categories within a dataset, which can be useful for various purposes such as data analysis, pattern recognition, and decision-making.

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  • 3. 
    One of them is? - ProProfs

    One of them is?

    • Supervised learning

    • Semi-supervised learning

    • Active learning

    • Reinforcement learning

    Correct Answer
    A. Supervised learning
    Explanation
    Supervised learning is a type of machine learning where the model is trained using labeled data, meaning that the input data is accompanied by the correct output. The model learns from this labeled data to make predictions or classify new, unseen data. In supervised learning, the algorithm learns from a known dataset and tries to generalize the patterns to make accurate predictions on new, unseen data. This is in contrast to other options like semi-supervised learning, active learning, and reinforcement learning, which have different approaches and objectives in training the model.

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  • 4. 
    Inputs are divided into how many in Classifications? - ProProfs

    Inputs are divided into how many in Classifications?

    • 2

    • 3

    • 4

    • 5

    Correct Answer
    A. 2
    Explanation
    The inputs are divided into two classifications.

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  • 5. 
    Who coined the name? - ProProfs

    Who coined the name?

    • Arthur Samuel

    • Jerry Samuel

    • Fredrick Samuel

    • Jacob Samuel

    Correct Answer
    A. Arthur Samuel
    Explanation
    Arthur Samuel is credited with coining the name.

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  • 6. 
    When was the name coined? - ProProfs

    When was the name coined?

    • 1987

    • 1959

    • 1978

    • 1990

    Correct Answer
    A. 1959
    Explanation
    The name was coined in 1959.

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  • 7. 
    What is the nationality of Arthur Samuel? - ProProfs

    What is the nationality of Arthur Samuel?

    • London

    • America

    • Netherlands

    • Poland

    Correct Answer
    A. America
    Explanation
    Arthur Samuel's nationality is America because the question asks for his nationality and America is the only option that represents a nationality.

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  • 8. 
    Where was the name coined? - ProProfs

    Where was the name coined?

    • IBM

    • MIT

    • Microsoft

    • Google headquarters

    Correct Answer
    A. IBM
    Explanation
    The name "IBM" was coined at IBM itself.

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  • 9. 
    Who provided a formal definition of machine learning? - ProProfs

    Who provided a formal definition of machine learning?

    • Tom A. Mitchell

    • Tom M. Mitchell

    • Tom K. Mitchell

    • Tom J. Mitchell

    Correct Answer
    A. Tom M. Mitchell
    Explanation
    Tom M. Mitchell provided a formal definition of machine learning.

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  • 10. 
    Machine learning is divided into how many categories? - ProProfs

    Machine learning is divided into how many categories?

    • 2

    • 3

    • 4

    • 5

    Correct Answer
    A. 2
    Explanation
    Machine learning is divided into two main categories: supervised learning and unsupervised learning. In supervised learning, the algorithm is trained on labeled data, where the input and the desired output are provided. The algorithm learns from this data to make predictions or decisions. In unsupervised learning, the algorithm is trained on unlabeled data, where there are no predefined outputs. The algorithm learns patterns and structures in the data to make sense of it. These two categories cover the majority of machine learning techniques and applications.

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  • Current Version
  • Oct 07, 2024
    Quiz Edited by
    ProProfs Editorial Team
  • Mar 12, 2018
    Quiz Created by
    Livyn
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