1 files changed, 0 insertions, 62 deletions
diff --git a/examples/src/main/r/logistic_regression.R b/examples/src/main/r/logistic_regression.R
deleted file mode 100644
index 2a86aa9816..0000000000
--- a/examples/src/main/r/logistic_regression.R
+++ /dev/null
@@ -1,62 +0,0 @@
-#
-# 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")