R: R Interface for the RAPIDS cuML Suite of Libraries

# R Interface for the RAPIDS cuML Suite of Libraries

## Documentation for package ‘cuda.ml’ version 0.3.3

- DESCRIPTION file.

## Help Pages

cuda.ml-package | cuda.ml
cuda.ml | cuda.ml
cuda_ml_agglomerative_clustering | Perform Single-Linkage Agglomerative Clustering.
cuda_ml_can_predict_class_probabilities | Determine whether a CuML model can predict class probabilities.
cuda_ml_dbscan | Run the DBSCAN clustering algorithm.
cuda_ml_elastic_net | Train a linear model using elastic regression.
cuda_ml_elastic_net.data.frame | Train a linear model using elastic regression.
cuda_ml_elastic_net.default | Train a linear model using elastic regression.
cuda_ml_elastic_net.formula | Train a linear model using elastic regression.
cuda_ml_elastic_net.matrix | Train a linear model using elastic regression.
cuda_ml_elastic_net.recipe | Train a linear model using elastic regression.
cuda_ml_fil_enabled | Determine whether Forest Inference Library (FIL) functionalities are enabled in the current installation of {cuda.ml}.
cuda_ml_fil_load_model | Load a XGBoost or LightGBM model file.
cuda_ml_inverse_transform | Apply the inverse transformation defined by a trained cuML model.
cuda_ml_is_classifier | Determine whether a CuML model is a classifier.
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_ivfflat | Build a specification for the "ivfflat" KNN query algorithm.
cuda_ml_knn_algo_ivfpq | Build a specification for the "ivfpq" KNN query algorithm.
cuda_ml_knn_algo_ivfsq | Build a specification for the "ivfsq" 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_logistic_reg | Train a logistic regression model.
cuda_ml_logistic_reg.data.frame | Train a logistic regression model.
cuda_ml_logistic_reg.default | Train a logistic regression model.
cuda_ml_logistic_reg.formula | Train a logistic regression model.
cuda_ml_logistic_reg.matrix | Train a logistic regression model.
cuda_ml_logistic_reg.recipe | Train a logistic regression model.
cuda_ml_ols | Train a OLS model.
cuda_ml_ols.data.frame | Train a OLS model.
cuda_ml_ols.default | Train a OLS model.
cuda_ml_ols.formula | Train a OLS model.
cuda_ml_ols.matrix | Train a OLS model.
cuda_ml_ols.recipe | Train a 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_rand_proj | Random projection for dimensionality reduction.
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_serialise | Serialize a CuML model
cuda_ml_serialize | Serialize a CuML model
cuda_ml_sgd | Train a MBSGD linear model.
cuda_ml_sgd.data.frame | Train a MBSGD linear model.
cuda_ml_sgd.default | Train a MBSGD linear model.
cuda_ml_sgd.formula | Train a MBSGD linear model.
cuda_ml_sgd.matrix | Train a MBSGD linear model.
cuda_ml_sgd.recipe | Train a MBSGD linear model.
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 using a trained cuML model.
cuda_ml_tsne | t-distributed Stochastic Neighbor Embedding.
cuda_ml_tsvd | Truncated SVD.
cuda_ml_umap | Uniform Manifold Approximation and Projection (UMAP) for dimension reduction.
cuda_ml_unserialise | Unserialize a CuML model state
cuda_ml_unserialize | Unserialize a CuML model state
cuML_major_version | Get the major version of the RAPIDS cuML shared library {cuda.ml} was linked to.
cuML_minor_version | Get the minor version of the RAPIDS cuML shared library {cuda.ml} was linked to.
has_cuML | Determine whether {cuda.ml} was linked to a valid version of the RAPIDS cuML shared library.
predict.cuda_ml_fil | Make predictions on new data points.
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 | Make predictions on new data points.
predict.cuda_ml_rand_forest | Make predictions on new data points.
predict.cuda_ml_svm | Make predictions on new data points.