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 →

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 from GitHub: remotes::install_github("mohd-musheer/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.