Here are the sample questions which will help you be familiar with SAS Viya Supervised Machine Learning Pipelines (A00-406) exam style and structure. We encourage you to try our Demo SAS Machine Learning Certification Practice Exam to measure your understanding of exam structure in an environment which simulates the SAS Certified Specialist - Machine Learning Using SAS Viya Certification test environment.
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SAS A00-406 Sample Questions:
01. Which statement is true regarding decision trees and models based on ensembles of trees?
a) In the gradient boosting algorithm, for all but the first iteration, the target is the residual from the previous decision tree model.
b) For a Forest model, the out-of-bag sample is simply the original validation data set from when the raw data partitioning took place.
c) In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.
d) A single decision tree will always be outperformed by a model based on an ensemble of trees.
02. When building a recommendation system, which type of filtering is based on the user's behavior and preferences?
a) Content-based filtering
b) Collaborative filtering
c) Matrix factorization
d) Singular Value Decomposition (SVD)
03. Refer to the exhibit below:
Based on the output from the Data Exploration node shown in the exhibit, which variable has the most thin tails (most platykurtic distribution)?
a) Logi_rfm4
b) Logi_rfm6
c) Logi_rfm8
d) Logi_rfm12
04. Which feature extraction method can take both interval variables and class variables as inputs?
a) Autoencoder
b) Principal component analysis
c) Singular value decomposition
d) Robust PCA
05. A project has been created and a pipeline has been run in Model Studio. Which project setting can you edit?
a) Advisor Options for missing values
b) Partition Data percentages
c) Rules for model comparison statistic
d) Event-based Sampling proportions
06. Refer to the treemap shown in the exhibit below:
Which statement is true about the tree map for a decision tree with a binary target?
a) The top bar represents the node with the highest probability of event.
b) The darker bars represent nodes with a lower probability of event.
c) The top bar represents the node with the highest count.
d) The wider bars represent nodes with a higher probability of event.
07. In natural language processing (NLP), what is a common preprocessing step for text data before building models?
a) Standardization
b) Tokenization
c) Principal Component Analysis (PCA)
d) One-Hot Encoding
08. Which statements are true for the F1 score?
(Choose 2.)
a) F1 score is calculated based on a depth value.
b) F1 score is calculated based on a cut off value.
c) F1 score is applicable to a model with a binary target.
d) F1 score is applicable to a model with an interval target.
09. What is the difference between a classification problem and a regression problem in machine learning?
a) Classification predicts categorical outcomes, while regression predicts numeric outcomes.
b) Classification is a type of regression problem.
c) Regression predicts categorical outcomes, while classification predicts numeric outcomes.
d) There is no difference; the terms are used interchangeably.
10. Given the following properties for a neural network model, which statement is true regrading hidden units in the model? The following SAS program is submitted:
a) There are no hidden units in the model.
b) The number of hidden units is 1.
c) The number of hidden units is 50.
d) The number of hidden units is 26.
Answers:
|
Question: 1 |
Answer: a |
Question: 2 |
Answer: b |
|
Question: 3 |
Answer: d |
Question: 4 |
Answer: a |
|
Question: 5 |
Answer: c |
Question: 6 |
Answer: c |
|
Question: 7 |
Answer: b |
Question: 8 |
Answer: b, c |
|
Question: 9 |
Answer: a |
Question: 10 |
Answer: d |
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