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NEW QUESTION: 1
顧客は、選択したサプライヤーのリストから特定のアイテムを頻繁に注文します。一部のサプライヤーは交渉価格でアイテムを提供しますが、他のサプライヤーは年間を通じて価格を変更します。
両方の要件に対処するには、Oracle Procurement Cloudでこのアイテムをどのように設定する必要がありますか？
A. 固定価格サプライヤーの契約購入契約と、変動価格サプライヤーの包括購入契約を作成します。
B. 変動価格サプライヤーの契約購入契約を作成し、固定価格サプライヤーのいかなる種類の契約も作成しません。
C. 固定価格サプライヤーの計画発注を作成し、変動価格サプライヤーのいかなる種類の契約も作成しません。
D. 交渉済み価格サプライヤーの包括購入契約と、さまざまな価格サプライヤーの契約購入契約を作成します。
Answer: D
NEW QUESTION: 2
Approximately what percentage of SAP worldwide installations are running on HP Converged Infrastructure?
A. 10%
B. 26%
C. 64%
D. 42%
Answer: D
Explanation:
Reference:http://h20219.www2.hp.com/enterprise/downloads/4AA4-3448ENW.pdf(page 1, see HP & SAP a shared history of storage innovation, first bullet)
NEW QUESTION: 3
SiteCall meeting has one more signaling interaction process of a terminal and GK than a common meeting; this process should comply with the H.225 protocol.
A. TRUE
B. FALSE
Answer: B
NEW QUESTION: 4
You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey.
What should you use as a feature?
A. the fare of individual taxi journeys
B. the number of taxi journeys in the dataset
C. the trip ID of individual taxi journeys
D. the trip distance of individual taxi journeys
Answer: D
Explanation:
Explanation
The label is the column you want to predict. The identified Features are the inputs you give the model to predict the Label.
Example:
The provided data set contains the following columns:
vendor_id: The ID of the taxi vendor is a feature.
rate_code: The rate type of the taxi trip is a feature.
passenger_count: The number of passengers on the trip is a feature.
trip_time_in_secs: The amount of time the trip took. You want to predict the fare of the trip before the trip is completed. At that moment, you don't know how long the trip would take. Thus, the trip time is not a feature and you'll exclude this column from the model.
trip_distance: The distance of the trip is a feature.
payment_type: The payment method (cash or credit card) is a feature.
fare_amount: The total taxi fare paid is the label.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/predict-prices