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NEW QUESTION: 1
You are producing a multiple linear regression model in Azure Machine Learning Studio.
Several independent variables are highly correlated.
You need to select appropriate methods for conducting effective feature engineering on all the data.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Use the Filter Based Feature Selection module
Filter Based Feature Selection identifies the features in a dataset with the greatest predictive power.
The module outputs a dataset that contains the best feature columns, as ranked by predictive power. It also outputs the names of the features and their scores from the selected metric.
Step 2: Build a counting transform
A counting transform creates a transformation that turns count tables into features, so that you can apply the transformation to multiple datasets.
Step 3: Test the hypothesis using t-Test
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/studio-module-reference/filter-based-feature-selection
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/build-counting-transform
NEW QUESTION: 2
Which two choices are solutions of the NSX portfolio (Choose two.)?
A. NSX Service Mesh
B. vRealize Automation
C. Tanzu Kubernetes Grid
D. vRealize Network Insight
E. NSX Distributed IDS/IPS
Answer: A,E
NEW QUESTION: 3
You need to recommend which ports must be configured on the hardware load balancer to meet the technical requirements.
Which TCP ports should you include in the recommendation?
A. 135, 443, and 8080
B. 443 and 4443
C. 80 and 8080
D. 80, 5060, and 5061
Answer: B