This repository contains a lightweight C library that provides various utilities for machine learning and artificial intelligence applications. The library aims to assist in developing algorithms for execution on edge devices. The current version includes functionalities for reading CSV files, generating confusion matrices, computing regression accuracy metrics, and implementing directed acyclic graphs (DAG).
- CSV file reader: Easily read and parse CSV files to extract data for machine learning tasks.
- Confusion matrix generator: Compute confusion matrices to evaluate classification model performance.
- Regression accuracy metrics: Calculate accuracy metrics for regression models.
- Directed Acyclic Graph (DAG) implementation: Implement and manipulate DAG structures for various applications.
- Generic N-dimensional array.
- Scikit-Learn :wlike interface for machine learning algorithms, with two clustering algorithms implementation (KMeans and KMedoids)
The current version of this library provides a basic set of utilities for machine learning and artificial intelligence applications. However, the library will continue to evolve and expand its functionalities. Future updates may include additional algorithms, optimizations for edge devices, and more lightweight utility functions.
This library is open-source and distributed under the MIT License. Feel free to use, modify, and distribute it as per the terms of the license.