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10 November 2025

  • curprev 17:1617:16, 10 November 2025 Brb talk contribs 1,209 bytes +1,209 <syntaxhighlight lang='r'> library(umap) # Load the built-in Iris dataset data(iris) # Separate the features (variables) from the species labels iris_features <- iris[, 1:4] iris_species <- iris[, 5] # Run UMAP, reducing the 4 dimensions down to 2 # n_neighbors: Controls how UMAP balances local vs. global structure. # min_dist: Controls how tightly points are packed together. iris_umap_results <- umap(iris_features, random_state = 42) # The result is a list. The actual 2D coordinates are...
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