QUESTION: 53

DRAG DROP (Drag and Drop is not supported)
You need to use Azure Machine Learning designer to build a model that will predict automobile prices.
Which type of modules should you use to complete the model? To answer, drag the appropriate modules to the correct locations. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
Note: Each correct selection is worth one point.
Select and Place:

See Explanation section for answer.

Answer(s): A

Explanation:

Box 1: Select Columns in Dataset
For Columns to be cleaned, choose the columns that contain the missing values you want to change. You can choose multiple columns, but you must use the same replacement method in all selected columns.
Example:

Box 2: Split data
Splitting data is a common task in machine learning. You will split your data into two separate datasets. One dataset will train the model and the other will test how well the model performed.

Box 3: Linear regression
Because you want to predict price, which is a number, you can use a regression algorithm. For this example, you use a linear regression model.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-train-score

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QUESTION: 54

Which type of machine learning should you use to identify groups of people who have similar purchasing habits?

classification
regression
clustering

Answer(s): C

Explanation:

Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset

Reference:

https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

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QUESTION: 55

HOTSPOT (Drag and Drop is not supported)
To complete the sentence, select the appropriate option in the answer area.
Hot Area:

See Explanation section for answer.

Answer(s): A

Explanation:

Regression is a machine learning task that is used to predict the value of the label from a set of related features.

Reference:

https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

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QUESTION: 56

Which metric can you use to evaluate a classification model?

true positive rate
mean absolute error (MAE)
coefficient of determination (R2)
root mean squared error (RMSE)

Answer(s): A

Explanation:

What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as a flat line from the bottom left to the top right corner. Worse than random would dip below the y=x line.

Reference:

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

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