Manifold learning is an approach to non-linear dimensionality reduction. Algorithms for this task are based on the idea that the dimensionality of many data ...

Manifold is a geometry library dedicated to creating and operating on manifold triangle meshes. A manifold mesh is a mesh that represents a solid object.

A class of unsupervised estimators that seeks to describe datasets as low-dimensional manifolds embedded in high-dimensional spaces.

A command-line tool to simplify creating custom service manifests for SMF on Solaris systems. Project details. Verified details.

Tools for analyzing Manifold Markets data. Currently has bindings for their API, and code for computing various accuracy metrics (Brier score, log score, ...

29 окт. 2024 г. · Manifold learning is the process of modeling manifold on which training instances lie. Let's quickly introduce manifold learning in python. The Curse of Dimensionality · What is Manifold Learning?

UMAP is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction.

Manifold learning using Locally Linear Embedding. SpectralEmbedding. Spectral embedding for non-linear dimensionality. Notes. For an example of using ...

The Manifold visualizer provides high dimensional visualization using manifold learning to embed instances described by many dimensions into 2.

8 июн. 2023 г. · A dimensionality reduction technique called manifold learning can be used to see high-dimensional data in lower-dimensional spaces.