# # 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/bisectingKmeans.R # Load SparkR library into your R session library(SparkR) # Initialize SparkSession sparkR.session(appName = "SparkR-ML-bisectingKmeans-example") # $example on$ t <- as.data.frame(Titanic) training <- createDataFrame(t) # Fit bisecting k-means model with four centers model <- spark.bisectingKmeans(training, Class ~ Survived, k = 4) # get fitted result from a bisecting k-means model fitted.model <- fitted(model, "centers") # Model summary head(summary(fitted.model)) # fitted values on training data fitted <- predict(model, training) head(select(fitted, "Class", "prediction")) # $example off$ sparkR.session.stop()