Topic 1 Question 192
A newspaper publisher has a table of customer data that consists of several numerical and categorical features, such as age and education history, as well as subscription status. The company wants to build a targeted marketing model for predicting the subscription status based on the table data.
Which Amazon SageMaker built-in algorithm should be used to model the targeted marketing?
Random Cut Forest (RCF)
XGBoost
Neural Topic Model (NTM)
DeepAR forecasting
ユーザの投票
コメント(6)
- 正解だと思う選択肢: B
B is correct. IMO A - No, Random cut forest is for anomaly detection B - Yes, exactly was XGBoost is good for. Binary classification based on a variety of input features C - No, NTM is unsupervised. The problem states the table already has subscription status, therefore we need a supervised algorithm D - No, DeepAR is used for time-series data
👍 5hichemck2022/11/29 - 正解だと思う選択肢: B
Whether subscription status is binary or multi-class XGBoost can handle the problem in this case problem.
👍 5Peeking2022/12/10 I think the answer is B. It looks like no time serials condition, so it may be not suitable to A and D.
👍 4dunhill2022/11/28
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