--- title: Dimensionality Reduction Meets Network Science:... description: UMAP's internal k-nearest-neighbor (kNN) graph, typically overlooked in favor of its 2D embedding, encodes the data manifold in high-dimensional space before... canonical: https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph | daily.dev og:description: UMAP's internal k-nearest-neighbor (kNN) graph, typically overlooked in favor of its 2D embedding, encodes the data manifold in high-dimensional space before... og:url: https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi og:image: https://api.daily.dev/og/posts/lzEKwn4BI.png og:image:alt: Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph **[Apple Machine Learning Research](https://daily.dev/sources/mlapple)** · 1 min read · 0 upvotes · 0 comments ## Summary UMAP's internal k-nearest-neighbor (kNN) graph, typically overlooked in favor of its 2D embedding, encodes the data manifold in high-dimensional space before projection distortion. Applying standard graph algorithms to this graph unlocks new analytical capabilities: PageRank identifies representative data points, k-core decomposition distinguishes dense core regions from sparse periphery, and clustering coefficient detects tight-knit neighborhoods. Evaluated on MNIST and Fashion MNIST, these graph-based analyses prove competitive with or complementary to purpose-built methods like k-medoids and HDBSCAN. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Dimension reduction](https://daily.dev/posts/dimension-reduction-izd7roptu) · R-bloggers · 0 upvotes · 0 comments - [Understanding t-SNE: Dimensionality Reduction Technique](https://daily.dev/posts/understanding-t-sne-dimensionality-reduction-technique-k0wghex5z) · DigitalOcean Community · 0 upvotes · 0 comments - [Clustering Unstructured Text with LLM Embeddings and HDBSCAN](https://daily.dev/posts/clustering-unstructured-text-with-llm-embeddings-and-hdbscan-cihptxhvk) · Machine Learning Mastery · 0 upvotes · 0 comments - [Medium](https://daily.dev/posts/medium-1lr9o8anu) · Medium · 0 upvotes · 0 comments - [PCA: an embedding shrink-ray](https://daily.dev/posts/pca-an-embedding-shrink-ray-ayowx3qqb) · Software Doug · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-visualization](https://daily.dev/tags/data-visualization) [View this post on daily.dev](https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph","url":"https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi"},"datePublished":"2026-08-02T07:03:17.193Z","dateModified":"2026-08-02T07:31:05.410Z","description":"UMAP's internal k-nearest-neighbor (kNN) graph, typically overlooked in favor of its 2D embedding, encodes the data manifold in high-dimensional space before...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8dda20dea5f9a8a0e25a1b7bb36a1a20?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8dda20dea5f9a8a0e25a1b7bb36a1a20?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Apple Machine Learning Research","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Apple Machine Learning Research","logo":"https://media.daily.dev/image/upload/s--mD-1uSe0--/f_auto,q_auto/v1785654191/logos/mlapple","url":"https://daily.dev/sources/mlapple"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/dimensionality-reduction-meets-network-science-sensemaking-on-umap-s-knn-graph-lzekwn4bi","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"machine-learning,data-visualization","timeRequired":"PT1M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Apple Machine Learning Research","item":"https://daily.dev/sources/mlapple"},{"@type":"ListItem","position":3,"name":"Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph"}]} ```