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NEW QUESTION: 1
Your database is in shutdown state. What will happend if you issue next command:
SQL> startup
A. instance started, DB opened and finally mounted
B. instance started and DB is mounted
C. instance started, DB mounted and finally opened
D. instance will started
Answer: C
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 2
Which one of the following user classification schemes best reflects what function or function performs?
A. group-based classification
B. rule-based classification
C. attribute-based classification
D. rank-based classification
E. role-based classification
Answer: E
Explanation:
Explanation/Reference:
Given the potentially large number of users of a system, access privileges are generally not assigned at the user level. Instead, users are assigned to groups (mimicking the organizational structure of a company), or roles (defined based on job functions that users perform), or some combination of the two.
Access privileges are then assigned to groups and/or roles. The most natural case is that they are assigned to roles, since roles align more closely with operations users naturally perform to accomplish their job. The industry term for this is Role-Based Access Control (RBAC). RBAC is more flexible than defining access rights based on usernames or static groups and enables an organization to be more versatile when allocating resources.
With RBAC the system must determine if the subject (user or client) is associated with a role that has been granted access to a resource. This process of user to role ascertainment is called role mapping.
Incorrect answers
B: Rule-based access control is very similar to fine-grained access control, where access is controlled by rules defined in policies. The twist is that rules might refer to each other.
For instance, access may be granted to resource/function A as long as it is not also granted to resource/ function B.
This form of control can be used to ensure that a group or individual is not given privileges that create a conflict of interest or inappropriate level of authority. For instance, the approver of expenses or purchases cannot be the same as the requestor.
C: Role is better here.
D: There are times when access should be based on characteristics the user has rather than the organization or roles to which the user belongs. For instance, a customer with premium status might be granted access to exclusive offers, and a sales representative that has achieved his target sales revenue might have access to certain perks. Such levels of status vary over time, making it difficult to manage access based on relatively static group or role assignments. Attribute-based access control offers a more dynamic method of evaluation. Decisions are based on attributes assigned to users, which are free to change as business events unfold. Access policies define the attributes and values a user must have, and access decisions are evaluated against the current values assigned to the user. Attributes can be used to support both course-grained and fine-grained authorization.
E: No such thing as rank-based classification
Reference: Oracle Reference Architecture, Security , Release 3.1

NEW QUESTION: 3
You need to implement early stopping criteria as suited in the model training requirements.
Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:
Explanation:

Explanation:
You need to implement an early stopping criterion on models that provides savings without terminating promising jobs.
Truncation selection cancels a given percentage of lowest performing runs at each evaluation interval. Runs are compared based on their performance on the primary metric and the lowest X% are terminated.
Example:
from azureml.train.hyperdrive import TruncationSelectionPolicy
early_termination_policy = TruncationSelectionPolicy(evaluation_interval=1, truncation_percentage=20, delay_evaluation=5) Incorrect Answers:
Bandit is a termination policy based on slack factor/slack amount and evaluation interval. The policy early terminates any runs where the primary metric is not within the specified slack factor / slack amount with respect to the best performing training run.
Example:
from azureml.train.hyperdrive import BanditPolicy
early_termination_policy = BanditPolicy(slack_factor = 0.1, evaluation_interval=1, delay_evaluation=5 References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters

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