'Rcpp' Integration for the 'mlpack' Library
k-Furthest-Neighbors Search
K-Means Clustering
k-Nearest-Neighbors Search
K-Rank-Approximate-Nearest-Neighbors (kRANN)
LARS
Simple Linear Regression and Prediction
Linear SVM is an L2-regularized support vector machine.
Large Margin Nearest Neighbors (LMNN)
Local Coordinate Coding
L2-regularized Logistic Regression and Prediction
K-Approximate-Nearest-Neighbor Search with LSH
Mean Shift Clustering
Serialize/Unserialize an mlpack model.
mlpack
Parametric Naive Bayes Classifier
Neighborhood Components Analysis (NCA)
Non-negative Matrix Factorization
Principal Components Analysis
Perceptron
Binarize Data
Descriptive Statistics
One Hot Encoding
Scale Data
Split Data
RADICAL
Random forests
Softmax Regression
Sparse Coding
R binding test
AdaBoost
Approximate furthest neighbor search
BayesianLinearRegression
Collaborative Filtering
DBSCAN clustering
Decision tree
Density Estimation With Density Estimation Trees
Fast Euclidean Minimum Spanning Tree
FastMKS (Fast Max-Kernel Search)
GMM Sample Generator
GMM Probability Calculator
Gaussian Mixture Model (GMM) Training
Hidden Markov Model (HMM) Sequence Generator
Hidden Markov Model (HMM) Sequence Log-Likelihood
Hidden Markov Model (HMM) Training
Hidden Markov Model (HMM) Viterbi State Prediction
Hoeffding trees
Image Converter
Kernel Density Estimation
Kernel Principal Components Analysis
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) <doi:10.21105/joss.05026>.
Useful links