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NEW QUESTION: 1
Which three options can an engineer select for a traffic policer in case the traffic rate is less than the conform burst? (Choose three.)
A. Keep the packet in the buffer.
B. Set the DSCP value and drop the packet.
C. Set the CoS value and drop the packet.
D. Set the QoS group and drop the packet.
E. Drop the packet.
F. Transmit the packet.
Answer: D,E,F

NEW QUESTION: 2
A company's statement of financial position includes non-current assets which are leased, the tax regime follows the accounting treatment.
Which cash flows should be discounted when evaluating the cost of lease finance?
A. Lease payments and implied interest.
B. Lease payments, tax relief on implied interest and tax relief on straight-line account depreciation.
C. Lease payments and straight-line accounting depreciation.
D. Lease payments, implied interested and straight-line accounting deprediation.
Answer: C

NEW QUESTION: 3
Which of the following devices can be used to offload outbound web server SSL encryption
overhead?
A. Content filter
B. Proxy server
C. VPN concentrator
D. NIPS
Answer: B

NEW QUESTION: 4
AccessibilityToHighway列の欠落データを置き換える必要があります。
Clean Missing Dataモジュールをどのように構成する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation:
Box 1: Replace using MICE
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or "Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Scenario: The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.
Box 2: Propagate
Cols with all missing values indicate if columns of all missing values should be preserved in the output.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data