DAC Machine Learning & Predictive Analytics 2

Question 1

A model achieves 99% accuracy on training data but only 62% on test data. What is the most likely problem?

Accepted Answer

Overfitting

Answer

A large gap between high training accuracy and low test accuracy is the classic signature of overfitting.

Question 2

Which technique is most appropriate for reducing overfitting in a decision tree?

Accepted Answer

Pruning the tree

Answer

Pruning removes branches that add little predictive power, reducing complexity and overfitting.

Question 3

In a confusion matrix for a fraud detection model, what does a false negative represent?

Accepted Answer

A fraudulent transaction missed by the model

Answer

A false negative is an actual positive (fraud) that the model incorrectly labeled as negative (legitimate).

Question 4

Which metric is best when the cost of missing positive cases is very high, such as disease screening?

Accepted Answer

Recall

Answer

Recall measures the proportion of actual positives caught, which matters most when missing them is costly.

Question 5

What is the primary purpose of feature scaling before applying k-nearest neighbors?

Accepted Answer

To ensure all features contribute equally to distance calculations

Answer

KNN relies on distance, so features on larger scales would otherwise dominate the calculation.

Data Analytics Certifications (DAC) Practice Test