Supercharge your R workflows with
VectorForgeML

The high-performance Machine Learning framework bridging the gap between R's simplicity and C++'s speed. Created by Mohd Musheer.

Documentation Installation

Blazing Fast C++ Backend

Optimized C++ backend with BLAS/LAPACK integration ensures your models train in record time with zero-copy data exchange.

Modular Pipeline Design

Pipeline-ready architecture with StandardScaler, PCA, and more — compatible with modern R standards.

Easy R API

Familiar syntax for data scientists with 30+ algorithms — from Random Forest to K-Means clustering.

Simple yet Powerful Machine Learning in R

Build complex ML pipelines with just a few lines of code. VectorForgeML handles the heavy lifting with its C++ engine.

✓ 30+ Algorithms — classification, regression, clustering
✓ Zero-copy data exchange between R and C++
✓ Native Pipeline support for end-to-end workflows
✓ Comprehensive metrics — accuracy, F1, precision, recall, R², RMSE
✓ Preprocessing tools — scalers, encoders, transformers

library(VectorForgeML)

# Create a pipeline
pipe <- Pipeline(
  steps = list(
    c("scaler", StandardScaler()),
    c("pca", PCA(n_components = 2)),
    c("model", LogisticRegression())
  )
)

# Train in milliseconds
pipe$fit(X_train, y_train)
preds <- pipe$predict(X_test)

Comprehensive Machine Learning Toolset

VectorForgeML provides a complete suite of ML algorithms implemented in C++ for maximum performance in R.

Random Forest

Ensemble learning method for classification and regression with bootstrap aggregation.

K-Means Clustering

Fast unsupervised clustering with optimized centroid initialization in C++.

Linear Regression

High-performance regression with BLAS-accelerated linear algebra for high-dimensional data.

View All 30+ Algorithms →

Now Officially on CRAN

VectorForgeML has been officially accepted and published on the Comprehensive R Archive Network (CRAN). The package has passed all CRAN checks and is now globally distributed through CRAN mirrors worldwide.

Install it directly in R with a single command:

install.packages("VectorForgeML")
library(VectorForgeML)

VectorForgeML has been assigned a DOI for academic citation:
DOI: 10.32614/CRAN.package.VectorForgeML

View on CRAN →

Open for Collaboration

VectorForgeML welcomes contributions from researchers, data scientists, and developers. Whether you are interested in research collaborations, performance optimization, or expanding the algorithm library, there are many ways to get involved.

Open to research collaborations in machine learning and high-performance computing
Contributions welcome — new algorithms, bug fixes, and documentation improvements
Active roadmap for performance optimization and algorithm expansion
Use GitHub Issues and Discussions to share ideas or report bugs

Contribute on GitHub →

Frequently Asked Questions

What is VectorForgeML?

VectorForgeML is a high-performance machine learning framework for R powered by an optimized C++ backend. It provides 30+ algorithms including Random Forest, PCA, K-Means, Linear Regression, and full Pipeline support, enabling you to train models in milliseconds.

How do I install VectorForgeML?

Install VectorForgeML directly from CRAN: install.packages("VectorForgeML"). You need R ≥ 4.0.0 and a C++ compiler. See the full installation guide for details.

What algorithms does VectorForgeML support?

VectorForgeML supports 30+ algorithms across classification, regression, clustering, and dimensionality reduction. See the full API reference for the complete list.

Who created VectorForgeML?

VectorForgeML was created by Mohd Musheer, a Full Stack Developer and ML Engineer. The project is open-source under the MIT License.

Why is VectorForgeML faster than other R ML libraries?

VectorForgeML achieves superior performance through its optimized C++ backend that uses zero-copy data exchange with R, BLAS/LAPACK integration for linear algebra operations, and memory-efficient std::vector implementations.

Is VectorForgeML free to use?

Yes, VectorForgeML is completely free and open-source under the MIT License. Use it in personal and commercial projects. View on GitHub.

Supercharge your R workflows with VectorForgeML