Which metric is commonly used to evaluate the performance of a classification ne

Practice Questions

Q1
Which metric is commonly used to evaluate the performance of a classification neural network?
  1. Mean Squared Error
  2. Accuracy
  3. R-squared
  4. F1 Score

Questions & Step-by-Step Solutions

Which metric is commonly used to evaluate the performance of a classification neural network?
  • Step 1: Understand that a classification neural network is a type of model that predicts categories or classes.
  • Step 2: Learn that when we want to see how well the model is performing, we need a way to measure its success.
  • Step 3: Know that 'accuracy' is a common metric used for this purpose.
  • Step 4: Realize that accuracy tells us the percentage of correct predictions made by the model out of all predictions.
  • Step 5: For example, if the model makes 100 predictions and 90 of them are correct, the accuracy is 90%.
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