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author | Joseph K. Bradley <joseph@databricks.com> | 2015-02-27 13:00:36 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-02-27 13:00:36 -0800 |
commit | d17cb2ba33b363dd346ac5a5681e1757decd0f4d (patch) | |
tree | b6bb3c0062df0d18e3121fcb12fc317627c52b72 /docs/mllib-linear-methods.md | |
parent | 57566d0af3008982a1e24a763ed2f6a700b40f8f (diff) | |
download | spark-d17cb2ba33b363dd346ac5a5681e1757decd0f4d.tar.gz spark-d17cb2ba33b363dd346ac5a5681e1757decd0f4d.tar.bz2 spark-d17cb2ba33b363dd346ac5a5681e1757decd0f4d.zip |
[SPARK-4587] [mllib] [docs] Fixed save,load calls in ML guide examples
Should pass spark context to save/load
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #4816 from jkbradley/ml-io-doc-fix and squashes the following commits:
83d369d [Joseph K. Bradley] added comment to save,load parts of ML guide examples
2841170 [Joseph K. Bradley] Fixed save,load calls in ML guide examples
Diffstat (limited to 'docs/mllib-linear-methods.md')
-rw-r--r-- | docs/mllib-linear-methods.md | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/docs/mllib-linear-methods.md b/docs/mllib-linear-methods.md index d9fc63b37d..ffbd7ef1bf 100644 --- a/docs/mllib-linear-methods.md +++ b/docs/mllib-linear-methods.md @@ -223,8 +223,9 @@ val auROC = metrics.areaUnderROC() println("Area under ROC = " + auROC) -model.save("myModelPath") -val sameModel = SVMModel.load("myModelPath") +// Save and load model +model.save(sc, "myModelPath") +val sameModel = SVMModel.load(sc, "myModelPath") {% endhighlight %} The `SVMWithSGD.train()` method by default performs L2 regularization with the @@ -308,8 +309,9 @@ public class SVMClassifier { System.out.println("Area under ROC = " + auROC); - model.save("myModelPath"); - SVMModel sameModel = SVMModel.load("myModelPath"); + // Save and load model + model.save(sc.sc(), "myModelPath"); + SVMModel sameModel = SVMModel.load(sc.sc(), "myModelPath"); } } {% endhighlight %} @@ -423,8 +425,9 @@ val valuesAndPreds = parsedData.map { point => val MSE = valuesAndPreds.map{case(v, p) => math.pow((v - p), 2)}.mean() println("training Mean Squared Error = " + MSE) -model.save("myModelPath") -val sameModel = LinearRegressionModel.load("myModelPath") +// Save and load model +model.save(sc, "myModelPath") +val sameModel = LinearRegressionModel.load(sc, "myModelPath") {% endhighlight %} [`RidgeRegressionWithSGD`](api/scala/index.html#org.apache.spark.mllib.regression.RidgeRegressionWithSGD) @@ -496,8 +499,9 @@ public class LinearRegression { ).rdd()).mean(); System.out.println("training Mean Squared Error = " + MSE); - model.save("myModelPath"); - LinearRegressionModel sameModel = LinearRegressionModel.load("myModelPath"); + // Save and load model + model.save(sc.sc(), "myModelPath"); + LinearRegressionModel sameModel = LinearRegressionModel.load(sc.sc(), "myModelPath"); } } {% endhighlight %} |