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. |