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In the context of supervised learning, what is a 'label'?

Practice Questions

Q1
In the context of supervised learning, what is a 'label'?
  1. The input feature of the model
  2. The output variable that the model is trying to predict
  3. The algorithm used for training
  4. The process of evaluating the model

Questions & Step-by-Step Solutions

In the context of supervised learning, what is a 'label'?
  • Step 1: Understand that supervised learning is a type of machine learning where we teach a model using examples.
  • Step 2: In supervised learning, we have two main components: input features and output labels.
  • Step 3: Input features are the data we provide to the model to help it learn (like images, text, or numbers).
  • Step 4: A label is the correct answer or output we want the model to predict (like 'cat' or 'dog' for an image).
  • Step 5: The model learns to associate the input features with the correct labels during training.
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