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NEW QUESTION: 1
モデル開発戦略を実装して、ユーザーが広告に反応する傾向を判断する必要があります。
どのテクニックを使用する必要がありますか？
A. 相対式分割モジュールを使用して、重心距離に基づいてデータを分割します。
B. 相対式分割モジュールを使用して、イベントまでの移動距離に基づいてデータを分割します。
C. 行の分割モジュールを使用して、重心距離に基づいてデータを分割します。
D. 行の分割モジュールを使用して、イベントまでの移動距離に基づいてデータを分割します。
Answer: A
Explanation:
Explanation
Split Data partitions the rows of a dataset into two distinct sets.
The Relative Expression Split option in the Split Data module of Azure Machine Learning Studio is helpful when you need to divide a dataset into training and testing datasets using a numerical expression.
Relative Expression Split: Use this option whenever you want to apply a condition to a number column. The number could be a date/time field, a column containing age or dollar amounts, or even a percentage. For example, you might want to divide your data set depending on the cost of the items, group people by age ranges, or separate data by a calendar date.
Scenario:
Local market segmentation models will be applied before determining a user's propensity to respond to an advertisement.
The distribution of features across training and production data are not consistent References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

NEW QUESTION: 2
Which of the following tools are used for footprinting?(Choose four.
A. Cheops
B. Neotrace
C. NSLookup
D. Sam Spade
E. Traceroute
Answer: B,C,D,E
Explanation:
All of the tools listed are used for footprinting except Cheops.

NEW QUESTION: 3
DRAG DROP


Answer:
Explanation: