R Interface for the RAPIDS cuML Suite of Libraries

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Documentation for package ‘cuda.ml’ version 0.4.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

cuda.ml-package	cuda.ml
bundle.cuda_ml_model	Bundle a cuda.ml model
bundle.cuda_ml_nvforest	Bundle a cuda.ml model
cuda.ml	cuda.ml
cuda_ml_agglomerative_clustering	Perform single-linkage agglomerative clustering.
cuda_ml_backend_info	Report native-backend metadata
cuda_ml_cache_clean	Remove cuda.ml native-backend caches
cuda_ml_dbscan	Run the DBSCAN clustering algorithm.
cuda_ml_elastic_net	Train a linear model using elastic net regression.
cuda_ml_elastic_net.data.frame	Train a linear model using elastic net regression.
cuda_ml_elastic_net.default	Train a linear model using elastic net regression.
cuda_ml_elastic_net.formula	Train a linear model using elastic net regression.
cuda_ml_elastic_net.matrix	Train a linear model using elastic net regression.
cuda_ml_elastic_net.recipe	Train a linear model using elastic net regression.
cuda_ml_install	Install a cuda.ml native backend
cuda_ml_inverse_transform	Transform data with a dimensionality-reduction model
cuda_ml_kmeans	Run the k-means clustering algorithm.
cuda_ml_knn	Build a KNN model.
cuda_ml_knn.data.frame	Build a KNN model.
cuda_ml_knn.default	Build a KNN model.
cuda_ml_knn.formula	Build a KNN model.
cuda_ml_knn.matrix	Build a KNN model.
cuda_ml_knn.recipe	Build a KNN model.
cuda_ml_knn_algo	Configure an approximate KNN query algorithm
cuda_ml_knn_algo_ivfflat	Configure an approximate KNN query algorithm
cuda_ml_knn_algo_ivfpq	Configure an approximate KNN query algorithm
cuda_ml_lasso	Train a linear model using LASSO regression.
cuda_ml_lasso.data.frame	Train a linear model using LASSO regression.
cuda_ml_lasso.default	Train a linear model using LASSO regression.
cuda_ml_lasso.formula	Train a linear model using LASSO regression.
cuda_ml_lasso.matrix	Train a linear model using LASSO regression.
cuda_ml_lasso.recipe	Train a linear model using LASSO regression.
cuda_ml_linear_reg	Train a regularized linear regression model
cuda_ml_logistic_reg	Train a logistic or multinomial regression model
cuda_ml_logistic_reg.data.frame	Train a logistic or multinomial regression model
cuda_ml_logistic_reg.default	Train a logistic or multinomial regression model
cuda_ml_logistic_reg.formula	Train a logistic or multinomial regression model
cuda_ml_logistic_reg.matrix	Train a logistic or multinomial regression model
cuda_ml_logistic_reg.recipe	Train a logistic or multinomial regression model
cuda_ml_nvforest_export	Export and import an nvForest checkpoint pair
cuda_ml_nvforest_import	Export and import an nvForest checkpoint pair
cuda_ml_nvforest_info	Inspect an nvForest model
cuda_ml_nvforest_leaf_ids	Return terminal leaf identifiers
cuda_ml_nvforest_load_model	Load a tree ensemble with nvForest
cuda_ml_nvforest_predict_per_tree	Return individual-tree predictions
cuda_ml_ols	Train an OLS model.
cuda_ml_ols.data.frame	Train an OLS model.
cuda_ml_ols.default	Train an OLS model.
cuda_ml_ols.formula	Train an OLS model.
cuda_ml_ols.matrix	Train an OLS model.
cuda_ml_ols.recipe	Train an OLS model.
cuda_ml_pca	Perform principal component analysis.
cuda_ml_rand_forest	Train a random forest model
cuda_ml_rand_forest.data.frame	Train a random forest model
cuda_ml_rand_forest.default	Train a random forest model
cuda_ml_rand_forest.formula	Train a random forest model
cuda_ml_rand_forest.matrix	Train a random forest model
cuda_ml_rand_forest.recipe	Train a random forest model
cuda_ml_ridge	Train a linear model using ridge regression.
cuda_ml_ridge.data.frame	Train a linear model using ridge regression.
cuda_ml_ridge.default	Train a linear model using ridge regression.
cuda_ml_ridge.formula	Train a linear model using ridge regression.
cuda_ml_ridge.matrix	Train a linear model using ridge regression.
cuda_ml_ridge.recipe	Train a linear model using ridge regression.
cuda_ml_runtime_audit	Audit the installed native backend
cuda_ml_serialize	Save and restore supported cuda.ml models
cuda_ml_sgd	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_sgd.data.frame	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_sgd.default	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_sgd.formula	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_sgd.matrix	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_sgd.recipe	Train a linear model using mini-batch stochastic gradient descent.
cuda_ml_svm	Train a SVM model.
cuda_ml_svm.data.frame	Train a SVM model.
cuda_ml_svm.default	Train a SVM model.
cuda_ml_svm.formula	Train a SVM model.
cuda_ml_svm.matrix	Train a SVM model.
cuda_ml_svm.recipe	Train a SVM model.
cuda_ml_transform	Transform data with a dimensionality-reduction model
cuda_ml_tsne	Perform t-distributed stochastic neighbor embedding.
cuda_ml_tsvd	Truncated SVD.
cuda_ml_umap	Uniform Manifold Approximation and Projection (UMAP) for dimension reduction.
cuda_ml_unserialize	Save and restore supported cuda.ml models
predict.cuda_ml_knn	Make predictions on new data points.
predict.cuda_ml_linear_model	Make predictions on new data points.
predict.cuda_ml_logistic_reg	Predict from a logistic or multinomial regression model
predict.cuda_ml_nvforest	Predict with an nvForest model
predict.cuda_ml_svm	Make predictions on new data points.