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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?**

**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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