Metadata-Version: 2.4
Name: rfx-fuse
Version: 1.0.0
Summary: RFX-Fuse: Breiman and Cutler's Unified ML Engine with GPU Acceleration
Home-page: https://github.com/chriskuchar/RFX-Fuse
Author: Chris Kuchar
Author-email: chrisjkuchar@gmail.com
Project-URL: Bug Reports, https://github.com/chriskuchar/RFX-Fuse/issues
Project-URL: Source, https://github.com/chriskuchar/RFX-Fuse
Project-URL: Documentation, https://github.com/chriskuchar/RFX-Fuse/blob/main/docs/API.md
Keywords: random forest,machine learning,gpu,cuda,classification,visualization,proximity
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: C++
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.19.0
Requires-Dist: pybind11>=2.6.0
Provides-Extra: dev
Requires-Dist: pytest>=6.0.0; extra == "dev"
Requires-Dist: pytest-cov>=2.10.0; extra == "dev"
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
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# RFX-Fuse: Breiman and Cutler's Unified ML Engine

[![PyPI](https://img.shields.io/pypi/v/rfx-fuse.svg)](https://pypi.org/project/rfx-fuse/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

**RFX-Fuse** delivers classification, regression, unsupervised learning, similarity search, explainability, and outlier detection from a single model.

## Installation

```bash
pip install rfx-fuse
```

**Prerequisites:** CMake 3.12+, Python 3.9+, C++17 compiler, CUDA 12.8+

## Quick Example

```python
import RFXFuse as rfx

clf = rfx.RandomForestClassifier(
    ntree=500,
    use_gpu=True,
    compute_importance=True,
    compute_proximity=True
)
clf.fit(X, y)

# OOB error (no separate test set needed)
oob_error = clf.get_oob_error()

# Overall importance
var_imp = clf.feature_importances_()
prox_imp = clf.get_proximity_importance()

# Local importance (per-sample) - e.g., for sample 0
local_var_imp = clf.get_local_importance()[0]      # why was sample 0 predicted this way?
local_prox_imp = clf.get_proximity_importance()[0] # why is sample 0 similar to neighbors?

# Similarity search with explanations
indices, scores, _, feat_idx, feat_imp = clf.get_top_k_similar_with_explanations(0, k=10)

# Outlier detection
outliers, scores = clf.compute_outliers(k=10)
```

## Documentation

- **GitHub**: https://github.com/chriskuchar/RFX-Fuse
- **API Reference**: https://github.com/chriskuchar/RFX-Fuse/blob/main/docs/API.md
- **Examples**: https://github.com/chriskuchar/RFX-Fuse/tree/main/examples

## CPU-Only Version

For systems without GPU: `pip install rfx-fuse-cpu`

## License

MIT License
