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MLS-C01 · Question #144

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…

The correct answer is B. XGBoost. XGBoost is a popular and powerful algorithm for binary classification problems such as this one, where the goal is to predict a binary outcome (e.g. whether a customer subscribes or not). It is particularly effective when the dataset has a mix of numerical and categorical…

Modeling

Question

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?

Options

  • ARandom Cut Forest (RCF)
  • BXGBoost
  • CNeural Topic Model (NTM)
  • DDeepAR forecasting

How the community answered

(40 responses)
  • A
    5% (2)
  • B
    88% (35)
  • C
    5% (2)
  • D
    3% (1)

Explanation

XGBoost is a popular and powerful algorithm for binary classification problems such as this one, where the goal is to predict a binary outcome (e.g. whether a customer subscribes or not). It is particularly effective when the dataset has a mix of numerical and categorical features.

Topics

#Binary Classification#XGBoost#SageMaker Built-in Algorithms#Tabular Data

Community Discussion

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