Project description

GhostUMAP

Installation

git clone https://github.com/jjmmwon/ghostumap.git
cd ghostumap
hatch shell

How to use GhostUMAP

from ghostumap import GhostUMAP
from sklearn.datasets import load_digits

digits = load_digits()

results = GhostUMAP().fit_transform(digits.data, n_embeddings=1, n_ghosts=4)

There are two parameters that are different from umap for the fit_transform method in the GhostUMAP class as follows:

n_embeddings: This determins the number of embeddings.

n_ghosts: This determins the number of ghosts.

Project details

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

0.0.1

Apr 30, 2024

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ghostumap-0.0.1.tar.gz (17.4 kB view hashes)

Uploaded Apr 30, 2024 Source

Built Distribution

ghostumap-0.0.1-py3-none-any.whl (18.6 kB view hashes)

Uploaded Apr 30, 2024 Python 3

Hashes for ghostumap-0.0.1.tar.gz

Hashes for ghostumap-0.0.1.tar.gz
Algorithm	Hash digest
SHA256	`a07d439f69cbb39be725a70700cd437499aa7070a9840fd67b78bf11bc587fa8`
MD5	`c83393f683c13fa229756a9e4d48d1ce`
BLAKE2b-256	`cc6eea7d4d7499e0fea401cb55b6694b16299456d632c513e6ea0160e9bcb353`

Hashes for ghostumap-0.0.1-py3-none-any.whl

Hashes for ghostumap-0.0.1-py3-none-any.whl
Algorithm	Hash digest
SHA256	`cf9b54c404bc10d8246822a32c340c3a4443402a08b647e3117c1b1affeb9822`
MD5	`3d59b3747ffc114c6b85d7193e300e9a`
BLAKE2b-256	`fc74a9dd2d93ba69b921072eb67fe729100265db210c3b21b78a1e4869542fa0`