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NEW QUESTION: 1

A. Option D
B. Option B
C. Option C
D. Option A
Answer: A
Explanation:
http://www.airheads.eu/aruba/attachments/aruba/Aruba-
VRDs/44/1/Aruba%20RAP%20VRD.pdf

NEW QUESTION: 2

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

NEW QUESTION: 3
Meredith Belbin carried out some notable research which concluded that successful teams need a good balance of complementary roles and personalities. His work concluded with the definition of nine distinctive roles that people adopt when working together in a team.
Applying this research, place the correct designated Belbin role label against the relevant personal characteristics.

Answer:
Explanation:

NEW QUESTION: 4
広告応答のモデリング戦略を定義する必要があります。
順番に実行する必要がある3つのアクションはどれですか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。

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