Imbalance Dataset 2

What is a prevalent problem while performing classification on datasets?

• Data imbalance

• Data science lifecycle

• Data democracy

• Data quality

Which factor affects the complexity of the concept represented by the data?

• Classification rules

• Feature space

• Class overlap

• Data distribution

What is the formula to calculate Imbalanced Ratio (IR)?

• (Total number of negative class examples) + (Total number of positive class examples)

• (Total number of positive class examples) / (Total number of negative class examples)

• (Total number of negative class examples) / (Total number of positive class examples)

• (Total number of positive class examples) - (Total number of negative class examples)

Which metric is used to measure the accuracy of a model in binary classification?

• F-measure

• Confusion Matrix

• Precision

• Recall

What method eliminates the majority class instances in the data to make it more balanced?

• Random Oversampling

• Tomek Links

• SMOTE

• Random Undersampling

Which method is based on a distance measure and removes majority class instances?

• Random Oversampling

• ADASYN

• Tomek Link

• SMOTE

Which oversampling method creates new instances based on interpolation between minority class instances?

• ADASYN

• Random Oversampling

• ENN

• SMOTE

What is the main focus of algorithmic-level approaches in dealing with imbalanced datasets?

• Feature engineering

• Balancing class distribution

• Modifying the classifier

• Modifying the dataset

Which technique focuses on removing noisy and borderline examples near the decision boundary in imbalanced datasets?

• Random Oversampling

• SMOTE

• ADASYN

• ENN

How does the F-measure combine precision and recall in binary classification evaluation?

• It takes the harmonic mean of precision and recall

• It calculates the average of precision and recall

• It multiplies precision and recall

• It divides precision by recall