rusty_math

This is a Rust library for mathematical, statistical and machine learning operations.

Version 0.7.0

New version now supports K-Means clustering. See clustering module for more details.

Features

• GCD
• LCM
• Factorial
• Check if a number is prime
• Find all primes numbers less than a number
• Permutation
• Combination
• Integration
• Differentiation
• Solve a linear equation
• Find roots of a polynomial using Falsi Reguli and Newton-Raphson methods
• Linear Regression
• Logistic Regression
• Lasso and Ridge Regression
• Logistic Regression
• Naive Bayes Classifier
• K-Nearest Neighbors
• K-Means Clustering
• R2 score
• Mean squared error
• Accuracy
• Precision
• Confusion Matrix
• Recall
• F1 score

Installation

To use rusty_math in your project, add the following to your Cargo.toml file:

[dependencies]
rusty_math = "0.7.0"

Modules

1. numbers: Functions to find the GCD, LCM, factorial, to check for prime, to find all prime numbers less than n.
2. calculus: Find the definite integral and slope of a function at a point.
3. Linear: Fit and predict a several types linear functions.
4. Equations: Solve a system of linear equations and find a root of polynomials using Falsi Reguli and Newton-Raphson methods
5. naive_bayes: Fit a Gaussian Naive Bayes classifier and predict classes.
6. knn: Fit and predict target values using K-nearest neighbors classification and regression models.
7. clustering: Clustering Algorithms like KMeans.
8. Metrics: Score machine learning models.

See detailed documation for list of functionalities in each module.

Usage

use rusty_math::gcd;

fn main() {
    let result = gcd(12, 15);
    println!("GCD of 12 and 15 is {}",result) ;
}

Contributing

Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request.

In case of any questions or feedback feel free to contact me at kjmakwana00@gmail.com

License

This project is licensed under the MIT License.