Repository: spark Updated Branches: refs/heads/master c48f2a3a5 -> 9c7f34af3
[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 <so...@cloudera.com> Closes #10675 from srowen/SPARK-5273. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/9c7f34af Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/9c7f34af Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/9c7f34af Branch: refs/heads/master Commit: 9c7f34af37ef328149c1d66b4689d80a1589e1cc Parents: c48f2a3 Author: Sean Owen <so...@cloudera.com> Authored: Tue Jan 12 12:13:32 2016 +0000 Committer: Sean Owen <so...@cloudera.com> Committed: Tue Jan 12 12:13:32 2016 +0000 ---------------------------------------------------------------------- docs/mllib-linear-methods.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/9c7f34af/docs/mllib-linear-methods.md ---------------------------------------------------------------------- diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md index 20b3561..aac8f75 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))) --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org