1 files changed, 62 insertions, 0 deletions
diff --git a/examples/src/main/r/logistic_regression.R b/examples/src/main/r/logistic_regression.R
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+++ b/examples/src/main/r/logistic_regression.R
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+#
+# 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.
+#
+
+library(SparkR)
+
+args <- commandArgs(trailing = TRUE)
+
+if (length(args) != 3) {
+  print("Usage: logistic_regression <file> <iters> <dimension>")
+  q("no")
+}
+
+# Initialize Spark context
+sc <- sparkR.init(appName = "LogisticRegressionR")
+iterations <- as.integer(args[[2]])
+D <- as.integer(args[[3]])
+
+readPartition <- function(part){
+  part = strsplit(part, " ", fixed = T)
+  list(matrix(as.numeric(unlist(part)), ncol = length(part[[1]])))
+}
+
+# Read data points and convert each partition to a matrix
+points <- cache(lapplyPartition(textFile(sc, args[[1]]), readPartition))
+
+# Initialize w to a random value
+w <- runif(n=D, min = -1, max = 1)
+cat("Initial w: ", w, "\n")
+
+# Compute logistic regression gradient for a matrix of data points
+gradient <- function(partition) {
+  partition = partition[[1]]
+  Y <- partition[, 1]  # point labels (first column of input file)
+  X <- partition[, -1] # point coordinates
+
+  # For each point (x, y), compute gradient function
+  dot <- X %*% w
+  logit <- 1 / (1 + exp(-Y * dot))
+  grad <- t(X) %*% ((logit - 1) * Y)
+  list(grad)
+}
+
+for (i in 1:iterations) {
+  cat("On iteration ", i, "\n")
+  w <- w - reduce(lapplyPartition(points, gradient), "+")
+}
+
+cat("Final w: ", w, "\n")