CompTIA DataX (DY0-001) — Question 50

A data scientist wants to predict a person's travel destination. The options are:
Branson, Missouri, United States

Mount Kilimanjaro, Tanzania -

Disneyland Paris, Paris, France -
Sydney Opera House, Sydney, Australia
Which of the following models would best fit this use case?

Answer options

• A. Linear discriminant analysis
• B. k-means modeling
• C. Latent semantic analysis
• D. Principal component analysis

Correct answer: A

Explanation

Linear discriminant analysis (LDA) is suitable for classifying data into distinct categories, making it the best choice for predicting travel destinations. The other options, such as k-means modeling, are more suited for clustering data rather than classification, while latent semantic analysis and principal component analysis are used for different purposes like topic modeling and dimensionality reduction, respectively.