h2o4gpu v0.2.0

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Interface to 'H2O4GPU'

Interface to 'H2O4GPU' <https://github.com/h2oai/h2o4gpu>, a collection of 'GPU' solvers for machine learning algorithms.

Readme

h2o4gpu - R Interface to H2O4GPU

This directory contains the R package for H2O4GPU. H2O4GPU is a collection of GPU solvers by H2Oai with APIs in Python and R. The Python API builds upon the easy-to-use scikit-learn API and its well-tested CPU-based algorithms. It can be used as a drop-in replacement for scikit-learn (i.e. import h2o4gpu as sklearn) with support for GPUs on selected (and ever-growing) algorithms. H2O4GPU inherits all the existing scikit-learn algorithms and falls back to CPU algorithms when the GPU algorithm does not support an important existing scikit-learn class option. The R package is a wrapper around the H2O4GPU Python package, and the interface follows standard R conventions for modeling.

Installation

First, please follow the instruction here to build the H2O4GPU Python package.

Then install h2o4gpu R package via the following:

if (!require(devtools)) install.packages("devtools")
devtools::install_github("h2oai/h2o4gpu", subdir = "src/interface_r")

To test your installation, try the following example that builds a simple XGBoost random forest classifier:

library(h2o4gpu)

# Setup dataset
x <- iris[1:4]
y <- as.integer(iris$Species) - 1

# Initialize and train the classifier
model <- h2o4gpu.random_forest_classifier() %>% fit(x, y)

# Make predictions
predictions <- model %>% predict(x)

For more examples, please visit the package vignettes.

Functions in h2o4gpu

Name Description
h2o4gpu.pca Principal Component Analysis (PCA)
h2o4gpu.gradient_boosting_regressor Gradient Boosting Regressor
fit.h2o4gpu_model Train an H2O4GPU Estimator
h2o4gpu.random_forest_classifier Random Forest Classifier
fit Generic Method to Train an H2O4GPU Estimator
h2o4gpu.random_forest_regressor Random Forest Regressor
h2o4gpu.kmeans K-means Clustering
h2o4gpu.truncated_svd Truncated Singular Value Decomposition (TruncatedSVD)
h2o4gpu h2o4gpu in R
predict.h2o4gpu_model Make Predictions using Trained H2O4GPU Estimator
h2o4gpu.elastic_net_classifier Elastic Net Classifier
reexports Objects exported from other packages
h2o4gpu.elastic_net_regressor Elastic Net Regressor
h2o4gpu.gradient_boosting_classifier Gradient Boosting Classifier
transform.h2o4gpu_model Transform a Dataset using Trained H2O4GPU Estimator
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Vignettes of h2o4gpu

Name
getting_started.Rmd
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Details

Type Package
License Apache License 2.0
URL https://github.com/h2oai/h2o4gpu
BugReports https://github.com/h2oai/h2o4gpu/issues
SystemRequirements Python (>= 3.6) with header files and shared library; H2O4GPU (https://github.com/h2oai/h2o4gpu)
Encoding UTF-8
LazyData true
RoxygenNote 6.0.1
VignetteBuilder knitr
NeedsCompilation no
Packaged 2018-03-23 15:25:46 UTC; terrytangyuan
Repository CRAN
Date/Publication 2018-03-23 17:04:51 UTC

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