unsupervised machine learning algorithms such as Generalized Linear
Models, Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox
Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic

'isolationforest.R' 'parse.R' 'export.R' 'edicts.R' 'models.R'
'coxph.R' 'coxphutils.R' 'kmeans.R' 'gbm.R' 'glm.R' 'glrm.R'

'import.R' 'isolationforest.R' 'parse.R' 'export.R' 'edicts.R'
'models.R' 'coxph.R' 'coxphutils.R' 'kmeans.R' 'gbm.R'
'generic.R' 'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'deeplearning.R'
'naivebayes.R' 'word2vec.R' 'w2vutils.R' 'locate.R' 'grid.R'

'generic.R' 'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'psvm.R'

Title: R Interface for the 'H2O' Scalable Machine Learning Platform
'coxph.R' 'coxphutils.R' 'kmeans.R' 'gbm.R' 'generic.R' 'glm.R'
'glrm.R' 'pca.R' 'svd.R' 'psvm.R' 'deeplearning.R'

'coxph.R' 'coxphutils.R' 'kmeans.R' 'gam.R' 'gbm.R' 'generic.R'
'glm.R' 'glrm.R' 'pca.R' 'svd.R' 'psvm.R' 'deeplearning.R'
'word2vec.R' 'w2vutils.R' 'locate.R' 'grid.R' 'segment.R'

Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests,
Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes,
Generalized Additive Models (GAM), Cox Proportional Hazards, K-Means, PCA,
Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).

Suggests: ggplot2 (>= 3.3.0), mlbench, Matrix, slam, bit64 (>= 0.9.7),
survival, DT, IRdisplay, htmltools, plotly, repr
'models.R' 'coxph.R' 'coxphutils.R' 'kmeans.R' 'gam.R' 'gbm.R'
'locate.R' 'grid.R' 'segment.R' 'predict.R' 'tf-idf.R'

person("Tomas", "Fryda", role = c("ctb")),

Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, Maximum R GLM (maxrglm),
'parse.R' 'export.R' 'edicts.R' 'models.R' 'coxph.R'
'coxphutils.R' 'kmeans.R' 'gam.R' 'anovaglm.R' 'gbm.R'
'generic.R' 'glm.R' 'glrm.R' 'maxrglm.R' 'pca.R' 'svd.R'

Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection,
'generic.R' 'glm.R' 'glrm.R' 'modelselection.R' 'pca.R' 'svd.R'