'Rcpp' Integration for the 'mlpack' Library

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Documentation for package ‘mlpack’ version 4.8.0

• DESCRIPTION file.

Help Pages

mlpack-package	mlpack
adaboost	AdaBoost
adaboost_classify	AdaBoost Prediction
adaboost_probabilities	AdaBoost Probability Prediction
adaboost_train	AdaBoost
approx_kfn	Approximate furthest neighbor search
bayesian_linear_regression	BayesianLinearRegression
bayesian_linear_regression_predict	BayesianLinearRegression Prediction
bayesian_linear_regression_train	BayesianLinearRegression Training
cf	Collaborative Filtering
dbscan	DBSCAN clustering
decision_tree	Decision tree
decision_tree_classify	Decision tree Prediction
decision_tree_probabilities	Decision tree Prediction
decision_tree_train	Decision tree training
det	Density Estimation With Density Estimation Trees
emst	Fast Euclidean Minimum Spanning Tree
fastmks	FastMKS (Fast Max-Kernel Search)
gmm_generate	GMM Sample Generator
gmm_probability	GMM Probability Calculator
gmm_train	Gaussian Mixture Model (GMM) Training
hmm_generate	Hidden Markov Model (HMM) Sequence Generator
hmm_loglik	Hidden Markov Model (HMM) Sequence Log-Likelihood
hmm_train	Hidden Markov Model (HMM) Training
hmm_viterbi	Hidden Markov Model (HMM) Viterbi State Prediction
hoeffding_tree	Hoeffding trees
image_converter	Image Converter
kde	Kernel Density Estimation
kernel_pca	Kernel Principal Components Analysis
kfn	k-Furthest-Neighbors Search
kmeans	K-Means Clustering
knn	k-Nearest-Neighbors Search
krann	K-Rank-Approximate-Nearest-Neighbors (kRANN)
lars	LARS
lars_predict	LARS Prediction
lars_train	LARS Training
linear_regression	Simple Linear Regression and Prediction
linear_regression_predict	Linear Regression Prediction
linear_regression_train	Simple Linear Regression
linear_svm	Linear SVM is an L2-regularized support vector machine.
lmnn	Large Margin Nearest Neighbors (LMNN)
local_coordinate_coding	Local Coordinate Coding
logistic_regression	L2-regularized Logistic Regression and Prediction
logistic_regression_classify	L2-regularized Logistic Regression Classification
logistic_regression_probabilities	L2-regularized Logistic Regression Probabilities
logistic_regression_train	L2-regularized Logistic Regression Training and Prediction
lsh	K-Approximate-Nearest-Neighbor Search with LSH
mean_shift	Mean Shift Clustering
mlpack	mlpack
nbc	Parametric Naive Bayes Classifier
nca	Neighborhood Components Analysis (NCA)
nmf	Non-negative Matrix Factorization
pca	Principal Components Analysis
perceptron	Perceptron
predict.mlpack_adaboost	AdaBoost Prediction
predict.mlpack_bayesian_linear_regression	BayesianLinearRegression
predict.mlpack_lars	LARS Prediction
predict.mlpack_linear_regression	Linear Regression Prediction
predict.mlpack_logistic_regression	L2-regularized Logistic Regression Classification
predict.mlpack_random_forest	Random Forests
preprocess_binarize	Binarize Data
preprocess_describe	Descriptive Statistics
preprocess_one_hot_encoding	One Hot Encoding
preprocess_scale	Scale Data
preprocess_split	Split Data
radical	RADICAL
random_forest	Random Forests
random_forest_classify	Random Forests Prediction
random_forest_probabilities	Random Forests Probabilities
random_forest_train	Random Forests train
Serialize	Serialize/Unserialize an mlpack model.
softmax_regression	Softmax Regression
sparse_coding	Sparse Coding
test_r_binding	R binding test
Unserialize	Serialize/Unserialize an mlpack model.