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NO.1 Which outlier treatment is not available in the Quality tab of the Data Audit output?
A. Coerce
B. Nullify
C. Recode
D. Discard
Answer: C

NO.2 Some data mining models such as Neural Net and Support Vector Machine models do not
provide
equations or rules to help analysts determine how the models use the input fields for prediction. If
you have a categorical target field and a continuous input field, which graphing technique could aid
with interpretation?
A. Distribution node
B. Histogram node
C. Plot node
D. Evaluation node

NO.3 Which values are available as Field Roles? (Choose three.)
A. Input
B. Target
C. Nominal
D. Partition
Answer: A,B,D

NO.4 Which nodes are best suited for revealing relationships between categorical (nominal, ordinal)
fields? (Choose two.)
A. Means node
B. Matrix node
C. Distribution node
D. Table node
Answer: B,C

NO.5 Assume you have four fields, 4, A, C and D and you wish to find the sum of the values even if
there are $null$ missing values in one or more fields. Which expression would accomplish this
task?
A. Sum_n((ABCIJ))
B. A+B+C+D
C. sum_n([A, B, C, D])
D. to_real(A) + to_real(B) + to_real(C) + to_real(D)
Answer: C

NO.6 Assume you have two data files: a personnel file with information about employees and a
second
file with information about performance categories. You will use IBM SPSS Modeler to merge the
files together using performance category as the key. However, there are inconsistencies in the
category keys used in both the personnel file and the performance file. In order to merge the files
together without losing information from either the personnel file or the performance category file,
you would use:
A. A full outer join.
B. An inner join.
C. A partial outer join.
D. An anti-join.
Answer: A

NO.7 True or false: business objectives are the origin & every data mining solution.
A. True
B. False
Answer: A