Classification Models

Which of the following is example of Classification Model?

• Stock Price Prediction

• Spam Filter

• Movie Recommendation

• Disease Prediction

A table used to A table use to measure how well a classification model is performing

• accuracy table
• performance graph
• confusion matrix
• ROC curve

The number of instances that were correctly predicted as negative

• False Negatives
• True Negatives
• False Positives
• True Positives

The rate at which a model correctly predicts positive instances

• Specificity
• F1 Score
• Precision
• Recall

Proportion of true positives detected out of all the actual positive instances.

• Recall
• Specificity
• F1 Score
• Precision

An ____________ is computed as the harmonic mean of precision and recall.

• Specificity
• Accuracy
• F1 score
• AUC score

What is the formula to calculate Recall?

• True Positives / (True Positives + False Negatives)

• True Positives / (True Positives + False Positives)

• (True Positives + False Positives) / Total Instances

• True Negatives / (True Negatives + False Positives)

In a binary classification problem, if a model has a Recall of 0.85, what does this indicate?

• The model has a high rate of false positives

• The model correctly identifies 85% of actual negatives

• The model is perfectly accurate

• The model correctly identifies 85% of actual positives

What is the primary difference between accuracy and precision in a classification model?

• Accuracy is calculated using true negatives, while precision is calculated using true positives.

• Accuracy measures overall correctness, while precision measures the correctness of positive predictions.

• Accuracy is more important than precision in all cases.

• Precision is always higher than accuracy.

In the context of error calculation, what does a Type I error represent?

• Correctly accepting a false null hypothesis

• Correctly rejecting a true null hypothesis

• Incorrectly accepting a false null hypothesis

• Incorrectly rejecting a true null hypothesis