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NEW QUESTION: 1
What is the primary reason for assigning role-based communities to routes advertised by different nodes?
A. Reduce complexity
B. Route filtering
C. Perform policy based routing
D. Prevent routing loops
Answer: B

NEW QUESTION: 2
Your Azure Machine Learning workspace has a dataset named real_estate_data. A sample of the data in the dataset follows.

You want to use automated machine learning to find the best regression model for predicting the price column.
You need to configure an automated machine learning experiment using the Azure Machine Learning SDK.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: training_data
The training data to be used within the experiment. It should contain both training features and a label column (optionally a sample weights column). If training_data is specified, then the label_column_name parameter must also be specified.
Box 2: validation_data
Provide validation data: In this case, you can either start with a single data file and split it into training and validation sets or you can provide a separate data file for the validation set. Either way, the validation_data parameter in your AutoMLConfig object assigns which data to use as your validation set.
Example, the following code example explicitly defines which portion of the provided data in dataset to use for training and validation.
dataset = Dataset.Tabular.from_delimited_files(data)
training_data, validation_data = dataset.random_split(percentage=0.8, seed=1) automl_config = AutoMLConfig(compute_target = aml_remote_compute, task = 'classification', primary_metric = 'AUC_weighted', training_data = training_data, validation_data = validation_data, label_column_name = 'Class' ) Box 3: label_column_name label_column_name:
The name of the label column. If the input data is from a pandas.DataFrame which doesn't have column names, column indices can be used instead, expressed as integers.
This parameter is applicable to training_data and validation_data parameters.
Incorrect Answers:
X: The training features to use when fitting pipelines during an experiment. This setting is being deprecated. Please use training_data and label_column_name instead.
Y: The training labels to use when fitting pipelines during an experiment. This is the value your model will predict. This setting is being deprecated. Please use training_data and label_column_name instead.
X_valid: Validation features to use when fitting pipelines during an experiment.
If specified, then y_valid or sample_weight_valid must also be specified.
Y_valid: Validation labels to use when fitting pipelines during an experiment.
Both X_valid and y_valid must be specified together.
exclude_nan_labels: Whether to exclude rows with NaN values in the label. The default is True.
y_max: y_max (float)
Maximum value of y for a regression experiment. The combination of y_min and y_max are used to normalize test set metrics based on the input data range. If not specified, the maximum value is inferred from the data.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig?view=azure-ml-py

NEW QUESTION: 3
Which of the following statements are true about the XACML standard and architecture?
A. XACML defines an XML schema used to represent rules for access control.
B. XACML defines a TCP protocol used to communicate messages between Policy Enforcement Points.
C. SAML assertions can be used to carry XACML authorization decisions.
D. The Policy Enforcement Point (PEP) is where permit / deny access decisions are made.
E. The Policy Information Point (PIP) provides information such as user attributes or environmental data that may be used to make access control decisions.
Answer: A,C,D,E
Explanation:
Explanation/Reference:
A: PEP - Policy Enforcement Point, where permit/deny access decisions are enforced.
B: PIP - Policy Information Point, where information can be retrieved to evaluate policy conditions. For example, a user's role or time of day may be needed by the PDP to make a policy decision.
C: eXtensible Access Control Markup Language (XACML) provides a standard way to represent access control policy information using XML. XAMCL defines access control policies in terms of rules, which in turn are defined to include a target, an effect, and a set of conditions.
XACML defines an XML schema used to represent rule
E: The SAML 2.0 profile of XACML 2.0 defines SAML assertions used to carry policies, policy queries and responses, authorization decisions, authorization query decisions and responses, and attribute assertions.
In this way SAML authentication, attribute, and authorization assertions are incorporated into the security framework to complement XACML.
Reference: Oracle Reference Architecture, Security , Release 3.1

NEW QUESTION: 4
Refer to the exhibit.

What data is expected by the POST /accounts endpoint?
A)

B)

C)

D)

A. Option A
B. Option C
C. Option D
D. Option B
Answer: C

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