Question 8What approach are you using when trying to increase the size of a minority class so that it is similar to the size of the majority class?1 pointRandom OversamplingOversamplingSynthetic OversamplingUndersampling
Question
Question 8What approach are you using when trying to increase the size of a minority class so that it is similar to the size of the majority class?1 pointRandom OversamplingOversamplingSynthetic OversamplingUndersampling
Solution
The approach you are using when trying to increase the size of a minority class so that it is similar to the size of the majority class is called Oversampling.
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Question 9What approach are you using when you create a new sample of a minority class that does not yet exist?1 pointOversamplingSynthetic OversamplingRandom OversamplingWeighting
How does boosting handle class imbalance?Review LaterBoosting oversamples the majority class to balance the classes.Boosting assigns higher weights to misclassified instances to focus on the minority class.Boosting assigns higher weights to correctly classified instances to focus on the minority class.Boosting uses undersampling to balance the classes.
Which of the following is NOT a common technique for handling imbalanced classes in data preprocessing?a.Undersamplingb.Oversamplingc.Stratified samplingd.Random sampling
Question 1These are all methods of dealing with unbalanced classes EXCEPT:1 pointDownsampling.Mix of in-sample and out-of-sample.Mix of downsampling and upsampling.Upsampling.
Which preprocessing step should be performed before addressing class imbalance in unsupervised learning?Review LaterOutlier detectionData scalingFeature selectionClustering
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