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SASInstitute A00-255 Exam Syllabus Topics:

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

Question 1

What is the average squared error in the training data?
Response:

A. 0.131583
B. 0.131709
C. 0.131208
D. 0.133665

Question 2

Assume in a data mining project that the task is to predict rankings of a target variable as accurately as possible. Which of the following should be used to judge prediction models?
Response:

A. Gini coefficient
B. KS statistic
C. misclassification
D. average squared error

Question 3

For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:

A. It looks for a set of colinear inputs that correlate with the target.
B. It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.
C. It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
D. It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.

Question 4

The number of neurons in this Neural Network model is which of the following:
Response:

A. 1
B. 4 or more
C. 3
D. 2

Question 5

How many hidden layers are generally needed in an MLP-based neural network to capture a discontinuous relationship between inputs and target?
Response:

A. no hidden layer, direct connection between inputs and output is preferred
B. two hidden layers
C. one hidden layer
D. three or more hidden layers

Solutions: