surfaces-onnx-files
Pre-trained ONNX surrogate models for the surfaces library.
Installation
This package is typically installed as a dependency of surfaces:
pip install surfaces[surrogates]
Or install directly:
pip install surfaces-onnx-files
Contents
This package provides pre-trained ONNX models for fast surrogate evaluation of machine learning test functions:
| Model | Description |
|---|---|
| k_neighbors_regressor | KNN regressor surrogate |
| k_neighbors_classifier | KNN classifier surrogate |
| gradient_boosting_regressor | Gradient boosting regressor surrogate |
Usage
Once installed, the surfaces library automatically detects and uses this package:
from surfaces import load_surrogate
surrogate = load_surrogate("k_neighbors_regressor")
if surrogate:
result = surrogate.predict({"n_neighbors": 5, "leaf_size": 30, ...})
License
MIT License - See LICENSE.
Metadata
Release files for surfaces-onnx-files 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| surfaces_onnx_files-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Release files / surfaces_onnx_files-0.0.1-py3-none-any.whl
| Download URL | surfaces_onnx_files-0.0.1-py3-none-any.whl |
|---|---|
| Size | 58.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3595e3f1e09fd5f3bbe5866b4526407130e5616edcf421657058e46549b6c8db
|
|
BLAKE2b-256 checksum How to use checksums |
99f4394f492a882707a8966ea18ff941f895634894807d0001a4016fb5011179
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.4
|