Skip to main content

A collection of general-purpose Progressive Samplers (Latin-Hypercube, Jittered, Multi Jittered, etc). Mainly for Hyperparameter search

Project description

Progressive Samplers

Python version Version codecov Master Develop License

Collection of progressive samplers for general use, mainly for Hyperparameter search

Install using pip

pip install prosamplers

Frequently Asked Questions

Some terminology explanations

What is a sampler?

A sampler is a method / algorithm that generates a sequence of points in a given search space

What is progressive?

A progressive sampler allows generating points on a point-by-point basis and does not required to say in advance how many points there need to be. They allow to ask for more points indefinetely, some only have a minimal memory footprint whereas other require complex memory mechanism

Why we need Progressive Samplers?

Most use cases may be solve with a simple Grid or Random search, but when dimensionality is not huge (< 100 or so dimensions) and the computation time for each point is really expensive, this alternative sampling methods could outperform naive methods as Grid or Random Search. As dimensionality increases, results tend to converge to those of Random Search

Usage

1+1
2

Project details


Download files

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

Source Distribution

prosamplers-0.0.83.tar.gz (5.5 kB view details)

Uploaded Source

Built Distribution

prosamplers-0.0.83-py3-none-any.whl (10.2 kB view details)

Uploaded Python 3

File details

Details for the file prosamplers-0.0.83.tar.gz.

File metadata

  • Download URL: prosamplers-0.0.83.tar.gz
  • Upload date:
  • Size: 5.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.8.7

File hashes

Hashes for prosamplers-0.0.83.tar.gz
Algorithm Hash digest
SHA256 ee2740ef658fa57d44a08e0eb9af2fa17e70fea5ceccb07860e641d97a523130
MD5 ba49df642264846737accc0961296196
BLAKE2b-256 8e19a3940885a2c8b56c5f30cffcc4446638159101a3fc6b4248b722c7e1eeb7

See more details on using hashes here.

File details

Details for the file prosamplers-0.0.83-py3-none-any.whl.

File metadata

  • Download URL: prosamplers-0.0.83-py3-none-any.whl
  • Upload date:
  • Size: 10.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.8.7

File hashes

Hashes for prosamplers-0.0.83-py3-none-any.whl
Algorithm Hash digest
SHA256 560f032f33bcea7449f73980482b88dbb492e3c30d8b9753a026cdbfe645bec3
MD5 436d49ecb2f88ed834e2a68651822feb
BLAKE2b-256 8f4e1dcc1f043353a7cc40d5c3bdb8d837586f08dcf63673d1617f19047845bf

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page