QUESTION: 21 Exam Topic: First Question sets

HOTSPOT (Drag and Drop is not supported)
Complete the sentence by selecting the correct option in the answer area.
Hot Area:

See Explanation section for answer.

Answer(s): A

Explanation:

Replace using Probabilistic PCA: Compared to other options, such as Multiple Imputation using Chained Equations (MICE), this option has the advantage of not requiring the application of predictors for each column. Instead, it approximates the covariance for the full dataset. Therefore, it might offer better performance for datasets that have missing values in many columns.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

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QUESTION: 22 Exam Topic: First Question sets

You have recently concluded the construction of a binary classification machine learning model.
You are currently assessing the model. You want to make use of a visualization that allows for precision to be used as the measurement for the assessment.
Which of the following actions should you take?

You should consider using Venn diagram visualization.
You should consider using Receiver Operating Characteristic (ROC) curve visualization.
You should consider using Box plot visualization.
You should consider using the Binary classification confusion matrix visualization.

Answer(s): D

Explanation:

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#confusion-matrix

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QUESTION: 23 Exam Topic: First Question sets

This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.
You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.
You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.
Recommendation: You configure the use of the value k=1.
Will the requirements be satisfied?

Answer(s): B

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QUESTION: 24 Exam Topic: First Question sets

DRAG DROP (Drag and Drop is not supported)
You are in the process of constructing a regression model.
You would like to make it a Poisson regression model. To achieve your goal, the feature values need to meet certain conditions.
Which of the following are relevant conditions with regards to the label data? Answer by dragging the correct options from the list to the answer area.
Select and Place:

See Explanation section for answer.

Answer(s): A

Explanation:

Poisson regression is intended for use in regression models that are used to predict numeric values, typically counts. Therefore, you should use this module to create your regression model only if the values you are trying to predict fit the following conditions:
- The response variable has a Poisson distribution.
- Counts cannot be negative. The method will fail outright if you attempt to use it with negative labels.
- A Poisson distribution is a discrete distribution; therefore, it is not meaningful to use this method with non-whole numbers.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/poisson-regression

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QUESTION: 21 Exam Topic: First Question sets

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QUESTION: 23 Exam Topic: First Question sets

QUESTION: 24 Exam Topic: First Question sets

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