Пакунок: umap-learn (0.4.5+dfsg-2)

Links for umap-learn

Debian Resources:

Download Source Package umap-learn:

Maintainers:

Debian Med Packaging Team (QA Page, Mail Archive)
Andreas Tille (QA Page)
Nilesh Patra (QA Page)

External Resources:

Homepage [github.com]

Similar packages:

Uniform Manifold Approximation and Projection

Uniform 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:

 1. The data is uniformly distributed on a Riemannian manifold;
 2. The Riemannian metric is locally constant (or can be
    approximated as such);
 3. The manifold is locally connected.

From these assumptions it is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low dimensional projection of the data that has the closest possible equivalent fuzzy topological structure.

Інші пакунки пов'язані з umap-learn

depends

recommends

suggests

enhances

dep: python3

Інтерактивна обʼєктно-орієнтована мова високого рівня (типова версія „python3“)
dep: python3-numba

native machine code compiler for Python 3
dep: python3-numpy

Швидкі методи для роботи з числовими масивами для мови Python 3
dep: python3-scipy

scientific tools for Python 3
dep: python3-sklearn

Python modules for machine learning and data mining - Python 3

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