SAS Institute A00-406 SAS Viya Supervised Machine Learning Pipelines Online Training
SAS Institute A00-406 Online Training
The questions for A00-406 were last updated at May 16,2024.
- Exam Code: A00-406
- Exam Name: SAS Viya Supervised Machine Learning Pipelines
- Certification Provider: SAS Institute
- Latest update: May 16,2024
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
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.
Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?
- A . MySQL
- B . MongoDB
- C . Oracle Database
- D . Microsoft SQL Server
What is the primary goal of A/B testing in the context of model deployment?
- A . To evaluate the model’s accuracy
- B . To compare two different versions of a model or strategy to determine which performs better
- C . To assess data quality
- D . To create synthetic data
What does the term "bias" in machine learning refer to?
- A . A model’s inability to generalize to new data
- B . Systematic errors that cause a model to consistently underpredict or overpredict
- C . The simplicity of a model
- D . The overall accuracy of a model
What is the significance of the "bias-variance trade-off" in machine learning?
- A . It represents the trade-off between underfitting and overfitting.
- B . It indicates the trade-off between accuracy and precision.
- C . It refers to the trade-off between the number of features and the model’s complexity.
- D . It is not relevant in machine learning.
What is the purpose of cross-validation in model building and evaluation?
- A . Splitting the dataset into training and testing sets
- B . Reducing the dataset size
- C . Assessing the model’s generalization performance
- D . Generating synthetic data
What is the purpose of a "canary release" in the context of model deployment?
- A . To assess data quality
- B . To deploy a new model version to a small subset of users or systems for testing
- C . To create synthetic data
- D . To evaluate model accuracy
When deploying a machine learning model, what is "model drift"?
- A . A sudden increase in the model’s accuracy
- B . A change in the distribution of the input data or target variable over time
- C . The process of feature extraction
- D . A measure of feature importance
Which algorithm is commonly used for decision-making tasks in classification models?
- A . K-Means
- B . Decision Trees
- C . Principal Component Analysis (PCA)
- D . Linear Regression
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