Pakiet: umap-learn (0.5.4+dfsg-1)

Odnośniki dla umap-learn

Zasoby systemu Debian:

Pobieranie pakietu źródłowego umap-learn:

Opiekunowie:

Zasoby zewnętrzne:

Strona internetowa [github.com]

Podobne pakiety:

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.

Inne pakiety związane z umap-learn

wymaga

poleca

sugeruje

enhances

dep: python3

Interaktywny, wysokopoziomowy i obiektowy język programowania (domyślna wersja Python 3)
dep: python3-numba

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

Fast array facility to the Python language (Python 3)
dep: python3-pandas

data structures for "relational" or "labeled" data
dep: python3-pynndescent

nearest neighbor descent for approximate nearest neighbors
dep: python3-scipy

Narzędzia naukowe dla Pythona 3
dep: python3-sklearn

Python modules for machine learning and data mining - Python 3
dep: python3-tqdm

fast, extensible progress bar for Python 3 and CLI tool

Pobieranie umap-learn

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