1 dépôt
Awesome GitHub RepositoriesSupervised Embedding Learning
Learning projection mappings that leverage labels to improve separation of known classes.
Distinct from Supervised Learning: Specifically learns a projection for visualization/separation, whereas the parent is general classification/regression
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Awesome Supervised Embedding Learning GitHub Repositories
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- lmcinnes/umap
lmcinnes/umap
8,215Voir sur GitHubThis project is a manifold learning and non-linear dimensionality reduction library used to project high-dimensional data into lower-dimensional spaces while preserving topological structure. It functions as a parametric embedding framework and a topological data visualization library for identifying clusters and patterns within complex datasets. The library distinguishes itself through parametric neural mapping, which uses neural networks to learn functional mappings that allow for out-of-sample projections and the reconstruction of original data. It supports supervised and semi-supervised d
Uses categorical labels during the projection process to improve class separation and reveal data structures.
Pythondimensionality-reductionmachine-learningtopological-data-analysis
