examples/src/main/r/ml/decisionTree.R

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# To run this example use
# ./bin/spark-submit examples/src/main/r/ml/decisionTree.R

# Load SparkR library into your R session
library(SparkR)

# Initialize SparkSession
sparkR.session(appName = "SparkR-ML-decisionTree-example")

# DecisionTree 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 DecisionTree classification model with spark.decisionTree
model <- spark.decisionTree(training, label ~ features, "classification")

# Model summary
summary(model)

# Prediction
predictions <- predict(model, test)
head(predictions)
# $example off:classification$

# DecisionTree 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 DecisionTree regression model with spark.decisionTree
model <- spark.decisionTree(training, label ~ features, "regression")

# Model summary
summary(model)

# Prediction
predictions <- predict(model, test)
head(predictions)
# $example off:regression$

sparkR.session.stop()