Keyword Analysis & Research: umap

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  • UMAP: Uniform Manifold Approximation and Projection for …

    readthedocs.io

    https://umap-learn.readthedocs.io/en/latest/

    WEBUniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. The algorithm is founded on three assumptions about the data. The data is uniformly distributed on Riemannian manifold;

    DA: 37 PA: 28 MOZ Rank: 31

  • Understanding UMAP - GitHub Pages

    github.io

    https://pair-code.github.io/understanding-umap/

    WEBUnderstanding UMAP. Dimensionality reduction is a powerful tool for machine learning practitioners to visualize and understand large, high dimensional datasets. One of the most widely used techniques for visualization is t-SNE, but its performance suffers with large datasets and using it correctly can be challenging.

    DA: 22 PA: 7 MOZ Rank: 86

  • How to Use UMAP — umap 0.5 documentation - Read the Docs

    readthedocs.io

    https://umap-learn.readthedocs.io/en/latest/basic_usage.html

    WEBUMAP is a general purpose manifold learning and dimension reduction algorithm. It is designed to be compatible with scikit-learn, making use of the same API and able to be added to sklearn pipelines. If you are already familiar with sklearn you should be able to use UMAP as a drop in replacement for t-SNE and other dimension reduction classes.

    DA: 35 PA: 25 MOZ Rank: 98

  • What is a UMAP? - Allen Institute

    alleninstitute.org

    https://alleninstitute.org/resource/what-is-a-umap/

    WEBWhat is a UMAP? This is a special type of graph, called a Uniform Manifold Approximation and Projection (UMAP). UMAPs are helpful ways of displaying many types of data and are often referred to as one type of dimensionality reduction tool.

    DA: 91 PA: 18 MOZ Rank: 23

  • How Exactly UMAP Works - Towards Data Science

    towardsdatascience.com

    https://towardsdatascience.com/how-exactly-umap-works-13e3040e1668

    WEBOct 3, 2019 · Today we are going to dive into an exciting dimension reduction technique called UMAP that dominates the Single Cell Genomics nowadays. Here, I will try to question the myth about UMAP as a too mathematical method, and explain it using simple language.

    DA: 7 PA: 35 MOZ Rank: 39

  • How UMAP Works — umap 0.5 documentation - Read the Docs

    readthedocs.io

    https://umap-learn.readthedocs.io/en/latest/how_umap_works.html

    WEBUMAP is an algorithm for dimension reduction based on manifold learning techniques and ideas from topological data analysis. It provides a very general framework for approaching manifold learning and dimension reduction, but can also provide specific concrete realizations. This article will discuss how the algorithm works in practice.

    DA: 99 PA: 91 MOZ Rank: 100

  • What is a UMAP plot? - Single Cell Discoveries

    scdiscoveries.com

    https://www.scdiscoveries.com/blog/knowledge/what-is-a-umap-plot/

    WEBJan 20, 2023 · UMAP is an algorithm that takes a high-dimensional dataset (such as a single-cell RNA dataset) and reduces it to a low-dimensional plot that retains much of the original information. Most, if not all, single-cell RNA sequencing datasets contain thousands of gene expression counts per individual cell.

    DA: 93 PA: 28 MOZ Rank: 84

  • [1802.03426] UMAP: Uniform Manifold Approximation and …

    arxiv.org

    https://arxiv.org/abs/1802.03426

    WEBFeb 9, 2018 · UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data.

    DA: 92 PA: 18 MOZ Rank: 7

  • and Related Beyond-Accuracy Perspectives - GitHub Pages

    github.io

    https://beyondaccuracy-userprofiling.github.io/tutorial-umap23/

    WEBOutline. This tutorial will take place on June 26, 2023 in Limassol, Cyprus, as part of the 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2023). Material. Slides. Github. Resource Folder ( no datasets) Datasets. Notebook 1: CatGCN. Notebook 2: RHGN. Notebook 3: Fairness. Notebook 4: FairGNN.

    DA: 44 PA: 26 MOZ Rank: 20

  • UMAP explained | The best dimensionality reduction? - YouTube

    youtube.com

    https://www.youtube.com/watch?v=6BPl81wGGP8

    WEBUMAP explained! The great dimensionality reduction algorithm in one video with a lot of visualizations and a little code.Uniform Manifold Approximation and P...

    DA: 89 PA: 29 MOZ Rank: 2