When creating machine learning models, a key initial step is to identify the type of model required. One of these is the classification model. Which of these statements define a classification model?

Question

Options

• AA type of machine learning model for distinguishing among two or more discrete values. E.g.
• BA type of machine learning model is a meta-model maker, which classifies algo-rithms based on
• CA type of machine learning model that outputs continuous (typically, floating-point) values. E.g.
• DA type of classic model approach that is less used today and which has been re-placed by the

• A
  88% (23)
• C
  8% (2)
• D
  4% (1)

Explanation

A classification model is a supervised machine learning model that predicts which discrete category (class) an input belongs to. Examples include spam/not-spam email detection, image recognition (cat/dog/bird), or disease diagnosis (positive/negative). Choice C describes a regression model, which outputs continuous numerical values. Choices B and D are fabricated or inaccurate descriptions not recognized in ML taxonomy.

No community discussion yet for this question.