Metadata-Version: 2.1
Name: LAVASET
Version: 0.1.0
Summary: LAVASET: Latent Variable Stochastic Ensemble of Trees. An ensemble method for correlated datasets with spatial, spectral, and temporal dependencies
Home-page: https://github.com/melkasapi/LAVASET
Author: Melpomeni Kasapi
Author-email: mk218@ic.ac.uk
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: numpy
Requires-Dist: setuptools
Requires-Dist: scipy
Requires-Dist: cython
Requires-Dist: joblib

# LAVASET

LAVASET (Latent Variable Stochastic Ensemble of Trees) is a Python package designed for ensemble learning in datasets with complex spatial, spectral, and temporal dependencies. It leverages advanced machine learning techniques to provide robust predictions, making it ideal for applications in remote sensing, time-series analysis, and beyond.

## Features

- **Efficient Handling of Correlated Data**: Optimized for datasets where traditional models struggle.
- **Cython-Powered Performance**: Critical computations are implemented in Cython for efficiency.
- **Cross-Platform Compatibility**: Tested and deployable across Linux, macOS, and Windows.

## Installation

You can install LAVASET directly from PyPI:

```bash
pip install lavaset
```

## Requirements
- Python >= 3.7
- NumPy
- pandas
- scikit-learn
- scipy
- Cython
- joblib

Cython and NumPy are incorporated as build dependencies for LAVASET and are pre-installed before the package setup. If you encounter any issues during installation, especially regarding Cython or NumPy, consider installing these packages manually before proceeding with the LAVASET installation.

# If you're a MacOS or Windows user

LAVASET is built on a Linux architecture that is compatible with various linux platforms via a Docker image, however if you want to install directly to a MacOS or Windows environment using the conda would be the easiest way to do it.

## Step 1: Create a Conda environment

First, create and activate the conda environment where you'll install the Linux-built packages.

```bash
conda create -n lavaset-env python=3.x
conda activate lavaset-env
```
## Step 2: Add the Conda-forge channel
Add the Conda-forge channel, which provides many pre-built packages for various platforms.

```bash 
conda config --add channels conda-forge
```
## Step 3: Install linux-built LAVASET

```bash 
conda install LAVASET=0.1.0=linux-64
```

## Contributing

Contributions to LAVASET are welcome! Please refer to the contributing guidelines for more information.

## License

LAVASET is released under the MIT License. See the LICENSE file for more details.

## Contact

For questions or feedback, please contact Melpi Kasapi at mk218@ic.ac.uk.

Visit our [GitHub repository](https://github.com/melkasapi/LAVASET) for more information and updates.
