Imbalance Dataset

Which technique is introduced to generate synthetic examples for the minority class?

• SMOTE

• Random oversampling

• ROC curves

• Random undersampling

What is the main goal of SMOTEBoost algorithm?

• To increase the sampling weights for the majority class

• To improve the accuracy of the majority class

• To introduce more noise in the dataset

• To reduce the bias towards the majority class

What is the purpose of ROC curves in evaluating classifier performance?

• To summarize classifier performance over a range of tradeoffs

• To calculate the accuracy of the classifier

• To balance the class distribution

• To generate synthetic examples for the minority class

Which measure combines the trade-offs of precision and recall?

• Precision and recall

• Cost-sensitive measures

• F-value

• ROC curves

What is the purpose of the confusion matrix in evaluating a classifier?

• To summarize classifier performance

• To balance the class distribution

• To generate synthetic examples

• To calculate the accuracy

What is the main issue with imbalanced datasets in classification?

• Overfitting

• Underfitting

• Biased sampling

• Class distribution

Which method combines bagging with oversampling for bioinformatics applications?

• SMOTEBoost

• Rare-Boost

• DataBoost

• Radivojac et al.

What is the purpose of the Area Under the ROC Curve (AUC) metric?

• To calculate the accuracy of the classifier

• To summarize classifier performance

• To balance the class distribution

• To identify optimal classifiers

Which technique is used to minimize the expected cost of making an error in classification?

• SMOTE

• ROC curves

• Cost curves

• Cost matrix

What is the purpose of the F1 score in evaluating a classifier?

• To summarize classifier performance

• To balance the class distribution

• To calculate the accuracy

• To combine precision and recall