DY0-001 · Question #87
A company created a very popular collectible card set. Collectors attempt to collect the entire set, but the availability of each card varies, with because some cards have higher production volumes…
The correct answer is D. Decision trees. You have categorical inputs (wrapper color, shape, animal) and a binary target (sea vs. land). A decision tree natively handles categorical features and yields clear, rule-based splits that predict habitat, making it the most appropriate choice.
Question
A company created a very popular collectible card set. Collectors attempt to collect the entire set, but the availability of each card varies, with because some cards have higher production volumes than others. The set contains a total of 12 cards. The attributes of the cards are below:
A data scientist is provided a historical record of cards purchased, which was acquired by a local collectors' association. The data scientist needs to design an initial model iteration to predict whether or not the animal on the card lives in the sea or on land given the provided attributes. Which of the following is the best way to accomplish this task?
Exhibit
Options
- AARIMA
- BLinear regression
- CAssociation rules
- DDecision trees
How the community answered
(31 responses)- A16% (5)
- B6% (2)
- C6% (2)
- D71% (22)
Explanation
You have categorical inputs (wrapper color, shape, animal) and a binary target (sea vs. land). A decision tree natively handles categorical features and yields clear, rule-based splits that predict habitat, making it the most appropriate choice.
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