C2090-930

C2090-930 practice questions, page 2 of 3, with answer review and explanations.

Question 6

A client has a business goal of increasing units sold by 10 percent. Which two data mining objectives would be consistent with their business goal? (Choose two.)

  1. Create a profile of customers most likely to default on their account.
  2. Create a profile of current high value customers' purchasing patterns.
  3. Reduce marketing costs.
  4. Determine which products should be grouped together on the shopping Web site.

Question 7

You have a data source which provides many fields needed for data scoring. Some of these fields are not needed after the scoring is complete for the rest of the stream to operate. Which node should be used to remove these fields?

  1. Filter node
  2. Select node
  3. Sample Node
  4. Type node

Question 8

You have a large amount of data from which you want to build a model. Although many of the records of data are complete, there are substantial amounts of records which contain missing data. The records containing incomplete information should be excluded from analysis. Which node will exclude the undesired records?

  1. Filler node
  2. Filter node
  3. Select node
  4. Aggregate node

Question 9

You have optimized four models that do not meet your performance goals. You believe that by mergingthese models together you would achieve better performance. Which node would allow you to accomplish this task?

  1. Aggregate node
  2. Reclassify node
  3. Regression node
  4. Ensemble node

Question 10

Which two statements are true about linear regression? (Choose two.)

  1. The estimation method of coefficient is ordinary least squares.
  2. Methods for variable entry and removal are Enter Stepwise, Forward, and Backward.
  3. The calculation of the predictor importance is based on Regression Sum-of-Squares.
  4. Adjusted R-Squared is not a measure for Goodness-of-Fit.