blob: bc654f1df7ab6d3d7135724896422c92e562fd00 [file] [log] [blame]
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# To run this example use
# ./bin/spark-submit examples/src/main/r/ml/gbt.R
# Load SparkR library into your R session
library(SparkR)
# Initialize SparkSession
sparkR.session(appName = "SparkR-ML-gbt-example")
# GBT classification model
# $example on:classification$
# Load training data
df <- read.df("data/mllib/sample_libsvm_data.txt", source = "libsvm")
training <- df
test <- df
# Fit a GBT classification model with spark.gbt
model <- spark.gbt(training, label ~ features, "classification", maxIter = 10)
# Model summary
summary(model)
# Prediction
predictions <- predict(model, test)
head(predictions)
# $example off:classification$
# GBT regression model
# $example on:regression$
# Load training data
df <- read.df("data/mllib/sample_linear_regression_data.txt", source = "libsvm")
training <- df
test <- df
# Fit a GBT regression model with spark.gbt
model <- spark.gbt(training, label ~ features, "regression", maxIter = 10)
# Model summary
summary(model)
# Prediction
predictions <- predict(model, test)
head(predictions)
# $example off:regression$
sparkR.session.stop()