Deep Recursive Embedding for High-Dimensional Data
Project description
# Deep Recursive Embedding
Deep Recursive Embedding (DRE) is a novel demensionality reduction method based on a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by a recursive training strategy. DRE makes use of the latent data representations for boosted embedding performance.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
DRE-1.0.6.tar.gz
(99.5 kB
view hashes)
Built Distribution
Close
Hashes for DRE-1.0.6-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 316c008ad5c75762b1459a73abd9aaf3f4f5e577f2d13746e677fad2c1d4dc5d |
|
MD5 | b015df4218b5d5ce05fbc4d03d675d65 |
|
BLAKE2b-256 | c4cc43774c0f53a290cede030d891933552fe7fa84f0207d1a9506eebf229727 |