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Exam DY0-001 topic 1 question 49 discussion

Actual exam question from CompTIA's DY0-001
Question #: 49
Topic #: 1
[All DY0-001 Questions]

A data scientist is building a model to predict customer credit scores based on information collected from reporting agencies. The model needs to automatically adjust its parameters to adapt to recent changes in the information collected. Which of the following is the best model to use?

  • A. Decision tree
  • B. Random forest
  • C. Linear discrimination analysis
  • D. XGBoost
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Suggested Answer: D 🗳️
by SuntzuLegacy at May 19, 2025, 9:45 a.m.

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SuntzuLegacy
1 month, 1 week ago
Selected Answer: D
Out of the listed options, XGBoost is generally the most straightforward to retrain incrementally (i.e., continuing from where it left off). While none of the four are “online” algorithms in the strictest sense, XGBoost provides a “warm start” capability that lets you update or fine-tune an existing model rather than retraining entirely from scratch. This makes it better suited to adapting more frequently to new data compared to a standard decision tree, random forest, or LDA approach.
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