MML Suggest plugin
This plugin provides a method to compile pipeline blueprints for new tasks.
Install
Note: this plugin depends on another plugin (mml-similarity) which is installed automatically - though this has no side effects.
pip install mml-suggest
Usage
To leverage existing models and task distances these must be reused:
mml suggest pivot.name=my_target_task +reuse.fed=my_distance_project reuse.models=[some_proj,another_proj,...]
This will compile a pipeline blueprint for my_target_task based on the fed task similarities from
my_distance_project leveraging all models previously trained in the specified projects.
To use the blueprint call
mml train pivot.name=my_target_task reuse.blueprint=my_blueprint_proj#the_blueprint_number mode.use_blueprint=true
Metadata
Release files for mml-suggest 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mml_suggest-0.3.1.tar.gz | 9.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mml_suggest-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.0 kB
Release files / mml_suggest-0.3.1.tar.gz
| Download URL | mml_suggest-0.3.1.tar.gz |
|---|---|
| Size | 9.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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twine/6.0.1 CPython/3.12.8
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Transparency logRelease files / mml_suggest-0.3.1-py3-none-any.whl
| Download URL | mml_suggest-0.3.1-py3-none-any.whl |
|---|---|
| Size | 9.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
5eb0f3194fd01b8dca25c160473de890b14d3883584e5b45eaac4a336c6ff868
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BLAKE2b-256 checksum How to use checksums |
477371b1715433e592aec7fe971a060aaded393aba0f39124b852201793538f9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.0.1 CPython/3.12.8
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 31, 2024.
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