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mlpack (version 4.8.0)

'Rcpp' Integration for the 'mlpack' Library

Description

A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. See also Curtin et al. (2023) .

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Version

Install

install.packages('mlpack')

Monthly Downloads

768

Version

4.8.0

License

BSD_3_clause + file LICENSE

Issues

7

Pull Requests

9

Stars

5,679

Forks

1,719

Maintainer

Ryan Curtin

Last Published

July 16th, 2026

Functions in mlpack (4.8.0)

hoeffding_tree

Hoeffding trees
hmm_generate

Hidden Markov Model (HMM) Sequence Generator
linear_svm

Linear SVM is an L2-regularized support vector machine.
image_converter

Image Converter
lmnn

Large Margin Nearest Neighbors (LMNN)
kfn

k-Furthest-Neighbors Search
kmeans

K-Means Clustering
linear_regression_train

Simple Linear Regression
predict.mlpack_linear_regression

Linear Regression Prediction
predict.mlpack_lars

LARS Prediction
hmm_train

Hidden Markov Model (HMM) Training
hmm_viterbi

Hidden Markov Model (HMM) Viterbi State Prediction
kde

Kernel Density Estimation
linear_regression

Simple Linear Regression and Prediction
lars

LARS
predict.mlpack_logistic_regression

L2-regularized Logistic Regression Classification
hmm_loglik

Hidden Markov Model (HMM) Sequence Log-Likelihood
krann

K-Rank-Approximate-Nearest-Neighbors (kRANN)
knn

k-Nearest-Neighbors Search
gmm_generate

GMM Sample Generator
lars_train

LARS Training
kernel_pca

Kernel Principal Components Analysis
mean_shift

Mean Shift Clustering
Serialize

Serialize/Unserialize an mlpack model.
logistic_regression

L2-regularized Logistic Regression and Prediction
local_coordinate_coding

Local Coordinate Coding
lsh

K-Approximate-Nearest-Neighbor Search with LSH
logistic_regression_train

L2-regularized Logistic Regression Training and Prediction
logistic_regression_probabilities

L2-regularized Logistic Regression Probabilities
radical

RADICAL
preprocess_split

Split Data
preprocess_binarize

Binarize Data
preprocess_describe

Descriptive Statistics
perceptron

Perceptron
pca

Principal Components Analysis
preprocess_one_hot_encoding

One Hot Encoding
preprocess_scale

Scale Data
softmax_regression

Softmax Regression
nmf

Non-negative Matrix Factorization
random_forest_classify

Random Forests Prediction
nbc

Parametric Naive Bayes Classifier
predict.mlpack_random_forest

Random Forests
nca

Neighborhood Components Analysis (NCA)
sparse_coding

Sparse Coding
mlpack

mlpack
random_forest_probabilities

Random Forests Probabilities
random_forest_train

Random Forests train
test_r_binding

R binding test
approx_kfn

Approximate furthest neighbor search
cf

Collaborative Filtering
adaboost_probabilities

AdaBoost Probability Prediction
bayesian_linear_regression_predict

BayesianLinearRegression Prediction
dbscan

DBSCAN clustering
bayesian_linear_regression

BayesianLinearRegression
adaboost_train

AdaBoost
adaboost

AdaBoost
adaboost_classify

AdaBoost Prediction
bayesian_linear_regression_train

BayesianLinearRegression Training
decision_tree_train

Decision tree training
decision_tree_probabilities

Decision tree Prediction
decision_tree

Decision tree
gmm_probability

GMM Probability Calculator
gmm_train

Gaussian Mixture Model (GMM) Training
fastmks

FastMKS (Fast Max-Kernel Search)
decision_tree_classify

Decision tree Prediction
det

Density Estimation With Density Estimation Trees
emst

Fast Euclidean Minimum Spanning Tree