Classification in Data Mining and Warehousing
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Questions and Answers

Supervised learning is a type of learning where the training data is accompanied by labels indicating the class of the observations. What is the purpose of the labels?

  • To predict the class of the observations (correct)
  • To classify new data based on the training set
  • To establish the existence of clusters in the data
  • To measure the performance of the model

    • What is the main difference between supervised and unsupervised learning?

  • Supervised learning requires labeled data, while unsupervised learning does not (correct)
  • Supervised learning uses clustering algorithms, while unsupervised learning uses classification algorithms
  • Supervised learning is more accurate than unsupervised learning
  • Supervised learning is used for regression tasks, while unsupervised learning is used for classification tasks

    • What is the aim of unsupervised learning?

  • To predict the class of the observations
  • To classify new data based on the training set
  • To establish the existence of clusters in the data (correct)
  • To measure the performance of the model

    • What is the process of classifying new data based on the training set called?

    <p>Classification</p> Signup and view all the answers

    Which algorithm is commonly used for classification based on decision trees?

    <p>Rule based classifier</p> Signup and view all the answers

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