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NEW QUESTION: 1
You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).
The remaining 1,000 rows represent class 1 (10 percent).
The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.
You need to configure the module.
Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: 300
You type 300 (%), the module triples the percentage of minority cases (3000) compared to the original dataset (1000).
Box 2: 5
We should use 5 data rows.
Use the Number of nearest neighbors option to determine the size of the feature space that the SMOTE algorithm uses when in building new cases. A nearest neighbor is a row of data (a case) that is very similar to some target case. The distance between any two cases is measured by combining the weighted vectors of all features.
By increasing the number of nearest neighbors, you get features from more cases.
By keeping the number of nearest neighbors low, you use features that are more like those in the original sample.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

NEW QUESTION: 2
You have an ASP.NET Web Forms application for processing orders.
Many users of the application submit their order forms multiple times due to incorrectly formatted credit card information.
You need to plan for validation of the length and format of data in the credit card field on the client side prior to processing each transaction.
Which approach should you recommend?
A. Use a Custom Validator control in the Page_Load method.
B. Use a Custom Validator control in the On Server Validate method
C. Use a Required Field Validator control and a Regular Expression Validator control.
D. Use a Required Field Validator control and a Compare Validator control.
Answer: C

NEW QUESTION: 3
Click the Exhibit button.
A parallel job is designed to Join data from two existing persisted data sets that were created in sort order using the join keys. You have optimized the job to leverage the existing sort order instead of resorting. Using the job score fragment shown in the exhibit for this job, how would you verify that this job is optimizing the sort operation?
A. The job is not optimized; there are inserted tsort operators.
B. The job is not optimized because the sort is inserted after the RemDup operator.
C. This cannot be verified from the job score. You must set the environment variable $DS_PX_DEBUG and verify the captured files.
D. The subargs property indicates that the sort is only checking sort order.
Answer: D