A00-225 Practice Online

A binary classifier is used to predict a rare event. Its performance is summarized in the following confusion matrix: | | Predicted Negative | Predicted Positive | |-||| | Actual Negative | 9750 | 250 | | Actual Positive | 25 | 75 | Given the model's performance, what is the False Positive Rate (FPR) of the classifier?

You are working on a predictive model and you notice that your categorical variable "Color" has 50 different levels, which is adding complexity to your model. You decide to group these levels into fewer categories based on their frequency of occurrence to improve the model’s interpretability and performance. What technique would you most likely use for this task?

You are building a predictive model using a dataset that contains numerous variables. Upon inspection, you notice a significant number of them are highly correlated. Which of the following actions is the MOST appropriate to address potential issues with irrelevant or redundant variables before proceeding with model building?

You are performing predictive modeling using a random forest technique in R through SAS Enterprise Miner. You want to examine variable importance to interpret the model. Which of the following commands within the R code can provide you with the variable importance measure typically associated with a random forest model?

In cluster analysis using parallel coordinate plots in SAS, how do you interpret a plot where clusters are shown with overlapping lines across multiple axes?