Exam DY0-001 topic 1 question 51 discussion

To predict a person’s travel destination from a discrete set of possible locations, you are looking at a supervised classification task. Linear discriminant analysis (LDA) is specifically designed for supervised classification with multiple classes. k-means is an unsupervised clustering method and would not be ideal if your destinations are already labeled. Latent semantic analysis (LSA) is typically used in text analysis to uncover hidden (latent) structures in textual data. Principal component analysis (PCA) is an unsupervised dimensionality-reduction technique, not primarily a classifier. Hence, for predicting a destination from a fixed set of categories, Linear discriminant analysis (Option A) would be the best choice.