📢 Too many exams? Don’t know which one suits you best? Book Your Free Expert 👉 call Now!
  • google app store apple app store
    • ✖

      Question

      The main difference between 'supervised' and

      'unsupervised' learning is that:
      A Supervised learning uses more data; unsupervised learning uses less data Correct Answer Incorrect Answer
      B Supervised learning uses labelled data; unsupervised learning uses unlabelled data Correct Answer Incorrect Answer
      C Supervised learning requires human intervention during every prediction; unsupervised learning is fully automated Correct Answer Incorrect Answer
      D Supervised learning is used only for classification; unsupervised learning is used only for regression Correct Answer Incorrect Answer
      E Supervised learning uses neural networks only; unsupervised learning uses decision trees only Correct Answer Incorrect Answer

      Solution

      Supervised learning uses labelled training data (features + target) for Classification (predict category — fraud/not fraud, default/no default) and Regression (predict continuous value — loan amount, house price). Algorithms of Supervised Learning are Linear/Logistic Regression, Decision Trees, SVM, Random Forest, Neural Networks. Unsupervised learning uses data with no labels for Clustering (K-Means, DBSCAN — customer segmentation), Dimensionality Reduction (PCA — compressing features) and Association Rules (Apriori — product bundling). In Banking, Supervised learning is used for credit scoring and Unsupervised learning is used for detecting unusual transaction clusters (potential fraud rings).

      Practice Next
      More Data Analytics Languages Questions

      Relevant for Exams:

      ask-question