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NEW QUESTION: 1
You work as a Firewall Analyst in the Tech Perfect Inc. The company has a Linux-based environment. You have installed and configured netfilter/iptables on all computer systems. What are the main features of netfilter/iptables?
Each correct answer represents a complete solution. Choose all that apply.
A. It includes many plug-ins or modules in 'patch-o-matic' repository
B. It includes a number of layers of API's for third party extensions
C. It offers stateless and stateful packet filtering with both IPv4 and IPv6 addressing schemes
D. It provides network address and port address translations with both IPv4 and IPv6 addressing schemes
Answer: A,B,C
NEW QUESTION: 2
Sie verwenden Windows Defender Advanced Threat Protection (Windows Defender ATP).
In der folgenden Tabelle sind die Windows Defender ATP-Computergruppen aufgeführt.
Sie planen, Computer wie in der folgenden Tabelle gezeigt in Windows Defender ATP zu integrieren.
Zu welcher Computergruppe wird jeder Computer hinzugefügt? Um zu antworten, wählen Sie die entsprechenden Optionen in der Antwort aus.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
NEW QUESTION: 3
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: 4
A comprehensive support approach in the application environment that spans the entire life cycle if IT solutions, from concept to phase-out.
This Support approach is known as :
Please choose the correct answer.
Response:
A. Assistance Management
B. Support Management
C. Application Lifecycle Management
D. Approach Management
Answer: C