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NEW QUESTION: 1
A customer is expanding from local storage to a SAN environment for the firt time. They plan to future proof their environment with a 16 Gb Fibre Channel. They also want to allow for future I/O expansion with new servers.
Identify the correct server and storage to meet the customer requirements.
Answer:
Explanation:
Explanation
Server model - HPE Proliant DL380 Gen10
Storage model - HPE MSA 2040
NEW QUESTION: 2
Which protocol maps IP network addresses to MAC hardware addresses so that IP packets can be sent across networks?
A. Address Resolution Protocol
B. Session Initiation Protocol
C. Transmission Control Protocol/Internet Protocol
D. Internet Control Message Protocol
Answer: A
NEW QUESTION: 3
Which two HTTP header fields relate to intrusion analysis? (Choose two).
A. user-agent
B. handshake type
C. connection
D. language
E. host
Answer: A,E
NEW QUESTION: 4
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-selec
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/build-counting-transform