Machine Learning week 6 quiz: Machine Learning System Design
阿新 • • 發佈:2019-01-30
You are working on a spam classification system using regularized logistic regression. "Spam" is a positive class (y = 1) and "not spam" is the negative class (y = 0). You have trained your classifier and there are m = 1000 examples in the cross-validation set. The chart of predicted class vs. actual class is:
Actual Class: 1 | Actual Class: 0 | |
Predicted Class: 1 | 85 | 890 |
Predicted Class: 0 | 15 | 10 |
For reference:
- Accuracy = (true positives + true negatives) / (total examples)
- Precision = (true positives) / (true positives + false positives)
- Recall = (true positives) / (true positives + false negatives)
- F1score = (2 * precision * recall) / (precision + recall)
What is the classifier's recall (as a value from 0 to 1)?
Enter your answer in the box below. If necessary, provide at least two values after the decimal point.