Knowee
Questions
Features
Study Tools

With the help of a confusion matrix, we can compute-(1 Point)RecallPrecisionAccuracyAll of the above

Question

With the help of a confusion matrix, we can compute-

  • Recall
  • Precision
  • Accuracy
  • All of the above
🧐 Not the exact question you are looking for?Go ask a question

Solution

All of the above. A confusion matrix is a table that is often used to describe the performance of a classification model (or "classifier") on a set of test data for which the true values are known. It allows the visualization of the performance of an algorithm.

  1. Accuracy: It is the ratio of the sum of true positive and true negative to the total population. It measures the proportion of correct predictions (both positive and negative) made by the model.

  2. Precision: It is the ratio of true positive to the sum of true positive and false positive. It measures the proportion of positive identifications that were actually correct.

  3. Recall: It is the ratio of true positive to the sum of true positive and false negative. It measures the proportion of actual positives that were identified correctly.

So, with the help of a confusion matrix, we can compute Recall, Precision, and Accuracy.

This problem has been solved

Similar Questions

With the help of a confusion matrix, we can compute-RecallPrecissionAccuracyAll of the above

For the given confusion matrix, compute the recall True Positive True NegativePredicted Positive 8 3Predicted Negative 2 7 0.73 0.7 0.78 0.8

Which metric should you use? SELECT ONLY ONE Duality Precision Recall Accuracy

Confusion matrix is an evaluation method used for 1 pointClassificationClusteringClassification and ClusteringRegression

Which of the following is NOT a classification metric used in Scikit-learn?(1 Point)PrecisionRecallF1-scoreR-squared

1/1

Upgrade your grade with Knowee

Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.