diff options
Diffstat (limited to 'docs')
-rw-r--r-- | docs/mllib-linear-methods.md | 8 |
1 files 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))) |