Metadata-Version: 2.1
Name: csa-prediction-engine
Version: 2.2.1
Summary: The csa_prediction_engine library provides a suite of tools and functions for performing relevance-based predictions using the Cambridge Sports Analytics Prediction Engine API. The package is designed to facilitate single and multi-task predictions, allowing for flexible model evaluation and experimentation.
Author: Cambridge Sports Analytics
Author-email: prediction@csanalytics.io
Description-Content-Type: text/markdown
Requires-Dist: numpy>=2.1
Requires-Dist: requests
Requires-Dist: csa-common-lib>=2.2.1

# Cambridge Sports Analytics Prediction Engine

Welcome to the **CSA Prediction Engine** package. This Python library provides a suite of tools and functions for performing relevance-based predictions using the Cambridge Sports Analytics (CSA) API. The package is designed to facilitate single and multi-task predictions, allowing for flexible model evaluation and experimentation.

## Key Features

- **Single Task Predictions**: Support for predictions with one dependent variable and one set of circumstances.
- **Multi-y Predictions**: Perform predictions with multiple dependent variables and a single set of circumstances.
- **Multi-theta Predictions**: Perform predictions with one dependent variable and multiple sets of circumstances.
- **Relevance-Based Grid Predictions**: Generate optimal predictions by evaluating all thresholds and variable combinations.
- **Grid Singularity Predictions**: Analyze grid predictions to find the singular optimal solution.
- **MaxFit Predictions**: Find the best-fit model based on adjusted relevance.


## Contributing

We welcome contributions to the CSA Relevance Engine package. If you find a bug or have a feature request, please reach out to the CSA support team: support@csanalytics.io

## License

(c) 2023 - 2024 Cambridge Sports Analytics, LLC. All rights reserved.
