From 9c7f34af37ef328149c1d66b4689d80a1589e1cc Mon Sep 17 00:00:00 2001
From: Sean Owen <sowen@cloudera.com>
Date: Tue, 12 Jan 2016 12:13:32 +0000
Subject: [PATCH] [SPARK-5273][MLLIB][DOCS] Improve documentation examples for
LinearRegression
Use a much smaller step size in LinearRegressionWithSGD MLlib examples to achieve a reasonable RMSE.
Our training folks hit this exact same issue when concocting an example and had the same solution.
Author: Sean Owen <sowen@cloudera.com>
Closes #10675 from srowen/SPARK-5273.
---
docs/mllib-linear-methods.md | 8 +++++---
1 file changed, 5 insertions(+), 3 deletions(-)
diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md
index 20b35612ca..aac8f7560a 100644
--- a/docs/mllib-linear-methods.md
+++ b/docs/mllib-linear-methods.md
@@ -590,7 +590,8 @@ val parsedData = data.map { line =>
// Building the model
val numIterations = 100
-val model = LinearRegressionWithSGD.train(parsedData, numIterations)
+val stepSize = 0.00000001
+val model = LinearRegressionWithSGD.train(parsedData, numIterations, stepSize)
// Evaluate model on training examples and compute training error
val valuesAndPreds = parsedData.map { point =>
@@ -655,8 +656,9 @@ public class LinearRegression {
// Building the model
int numIterations = 100;
+ double stepSize = 0.00000001;
final LinearRegressionModel model =
- LinearRegressionWithSGD.train(JavaRDD.toRDD(parsedData), numIterations);
+ LinearRegressionWithSGD.train(JavaRDD.toRDD(parsedData), numIterations, stepSize);
// Evaluate model on training examples and compute training error
JavaRDD<Tuple2<Double, Double>> valuesAndPreds = parsedData.map(
@@ -706,7 +708,7 @@ data = sc.textFile("data/mllib/ridge-data/lpsa.data")
parsedData = data.map(parsePoint)
# Build the model
-model = LinearRegressionWithSGD.train(parsedData)
+model = LinearRegressionWithSGD.train(parsedData, iterations=100, step=0.00000001)
# Evaluate the model on training data
valuesAndPreds = parsedData.map(lambda p: (p.label, model.predict(p.features)))
--
GitLab