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For implementing dimensional reduction, which method would be most effective when dealing with highly nonlinear data?
For implementing dimensional reduction, which method would be most effective when dealing with highly nonlinear data?
A . Linear Discriminant Analysis (LDA)
B . PCA
C . t-Distributed Stochastic Neighbor Embedding (t-SNE)
D . Factor Analysis
Answer: C
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