Question 21

You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.
How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Question 22

You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data.
You need to select a data cleaning method.
Which method should you use?
  • Question 23

    You use Azure Machine Learning to deploy a model as a real-time web service.
    You need to create an entry script for the service that ensures that the model is loaded when the service starts and is used to score new data as it is received.
    Which functions should you include in the script? To answer, drag the appropriate functions to the correct actions. Each function 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.

    Question 24

    You are performing a filter-based feature selection for a dataset to build a multi-class classifier by using Azure Machine Learning Studio.
    The dataset contains categorical features that are highly correlated to the output label column.
    You need to select the appropriate feature scoring statistical method to identify the key predictors.
    Which method should you use?
  • Question 25

    You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data.
    You need to select a data cleaning method.
    Which method should you use?