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NEW QUESTION: 1
공식적으로 검토를 종료하기 전에 피 청강자와 만나는 주된 목적은 다음과 같습니다.
A. 감사관이 중요한 문제를 간과하지 않았음을 확인하십시오.
B. 최종 프리젠 테이션의 구조를 테스트합니다.
C. 결과에 동의하십시오.
D. 감사 절차의 적절성에 대한 피드백을 받는다.
Answer: C
Explanation:
설명:
공식적으로 검토를 종결하기 전에 피 청강자와의 회의의 주된 목적은 결과에 대해 합의하는 것입니다. 다른 선택 사항은 감사의 공식적인 종결과 관련이 있지만 2 차적으로 중요합니다.
NEW QUESTION: 2
Bubba's margin account has securities valued at $20,000 and an $8,000 credit balance. What is the
equity in Bubba's account?
A. $28,000
B. $8,080
C. $12,800
D. $20,000
Answer: A
Explanation:
$28,000. The equity is the market value plus the credit balance.
NEW QUESTION: 3
You are performing sentiment analysis using a CSV file that includes 12,000 customer reviews written in a short sentence format. You add the CSV file to Azure Machine Learning Studio and configure it as the starting point dataset of an experiment. You add the Extract N-Gram Features from Text module to the experiment to extract key phrases from the customer review column in the dataset.
You must create a new n-gram dictionary from the customer review text and set the maximum n-gram size to trigrams.
What should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Vocabulary mode: Create
For Vocabulary mode, select Create to indicate that you are creating a new list of n-gram features.
N-Grams size: 3
For N-Grams size, type a number that indicates the maximum size of the n-grams to extract and store. For example, if you type 3, unigrams, bigrams, and trigrams will be created.
Weighting function: Leave blank
The option, Weighting function, is required only if you merge or update vocabularies. It specifies how terms in the two vocabularies and their scores should be weighted against each other.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/extract-n-gram-features-from-