Which metric is commonly used to evaluate the performance of a neural network on

Practice Questions

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

Questions & Step-by-Step Solutions

Which metric is commonly used to evaluate the performance of a neural network on a classification task?
  • Step 1: Understand that a neural network is a type of model used for making predictions.
  • Step 2: Know that in classification tasks, the goal is to categorize data into different classes or labels.
  • Step 3: Learn that to evaluate how well the neural network is performing, we need a metric.
  • Step 4: Recognize that 'accuracy' is a common metric used for this purpose.
  • Step 5: Understand that accuracy measures the proportion of correct predictions made by the model compared to the total predictions.
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