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NEW QUESTION: 1
Which statement is true related to job plan revisions?
A. When a job plan has been revised, IBM Maximo Asset Management V7.5 tracks all changes from previous versions. These changes are available for viewing from Select Action > View Revision History.
B. A job plan must be in a status of DRAFT or PNDREV for updates and edits to the job plan tab.
C. When a job plan is revised, all existing work orders with the job plan attached are updated with the revised version.
D. Caution must be used to select the most recent job plan revision when applying a job plan to a work order or preventive maintenance record.
Answer: B
NEW QUESTION: 2
View Exhibit 1 and examine the structure of the EMP and dept tables.
View Exhibit2 and examine the trigger code that is defined on the dept table to enforce the update and delete restrict referential actions on the primary key of the dept table.
What is the outcome on compilation?
A. It gives an error on compilation because the exception section Is used in the trigger.
B. It compiles and executes successfully.
C. It gives an error on compilation because it is not a row-level trigger.
D. It compiles successfully but gives an error on execution because it is not a row-level trigger.
Answer: C
NEW QUESTION: 3
You need to define a modeling strategy for ad response.
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: Implement a K-Means Clustering model
Step 2: Use the cluster as a feature in a Decision jungle model.
Decision jungles are non-parametric models, which can represent non-linear decision boundaries.
Step 3: Use the raw score as a feature in a Score Matchbox Recommender model The goal of creating a recommendation system is to recommend one or more "items" to "users" of the system. Examples of an item could be a movie, restaurant, book, or song. A user could be a person, group of persons, or other entity with item preferences.
Scenario:
Ad response rated declined.
Ad response models must be trained at the beginning of each event and applied during the sporting event.
Market segmentation models must optimize for similar ad response history.
Ad response models must support non-linear boundaries of features.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/multiclass-decision-jungle
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/score-matchbox-recommender