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| author | Sean Owen <sowen@cloudera.com> | 2016-05-26 14:25:28 -0700 |
|---|---|---|
| committer | Joseph K. Bradley <joseph@databricks.com> | 2016-05-26 14:25:28 -0700 |
| commit | b0a03feef2cf4daa7642ec7f4dc479dbd473b581 (patch) | |
| tree | 0d974e9a1badbe412a02c7bae91da2f3e98c2666 /examples/src/main/java | |
| parent | 0f61d6efb45b9ee94fa663f67c4489fbdae2eded (diff) | |
| download | spark-b0a03feef2cf4daa7642ec7f4dc479dbd473b581.tar.gz spark-b0a03feef2cf4daa7642ec7f4dc479dbd473b581.tar.bz2 spark-b0a03feef2cf4daa7642ec7f4dc479dbd473b581.zip | |
[SPARK-15457][MLLIB][ML] Eliminate some warnings from MLlib about deprecations
## What changes were proposed in this pull request?
Several classes and methods have been deprecated and are creating lots of build warnings in branch-2.0. This issue is to identify and fix those items:
* WithSGD classes: Change to make class not deprecated, object deprecated, and public class constructor deprecated. Any public use will require a deprecated API. We need to keep a non-deprecated private API since we cannot eliminate certain uses: Python API, streaming algs, and examples.
* Use in PythonMLlibAPI: Change to using private constructors
* Streaming algs: No warnings after we un-deprecate the classes
* Examples: Deprecate or change ones which use deprecated APIs
* MulticlassMetrics fields (precision, etc.)
* LinearRegressionSummary.model field
## How was this patch tested?
Existing tests. Checked for warnings manually.
Author: Sean Owen <sowen@cloudera.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #13314 from jkbradley/warning-cleanups.
Diffstat (limited to 'examples/src/main/java')
2 files changed, 3 insertions, 5 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/mllib/JavaLogisticRegressionWithLBFGSExample.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaLogisticRegressionWithLBFGSExample.java index 9d8e4a90db..7fc371ec0f 100644 --- a/examples/src/main/java/org/apache/spark/examples/mllib/JavaLogisticRegressionWithLBFGSExample.java +++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaLogisticRegressionWithLBFGSExample.java @@ -65,8 +65,8 @@ public class JavaLogisticRegressionWithLBFGSExample { // Get evaluation metrics. MulticlassMetrics metrics = new MulticlassMetrics(predictionAndLabels.rdd()); - double precision = metrics.precision(); - System.out.println("Precision = " + precision); + double accuracy = metrics.accuracy(); + System.out.println("Accuracy = " + accuracy); // Save and load model model.save(sc, "target/tmp/javaLogisticRegressionWithLBFGSModel"); diff --git a/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java index 5247c9c748..e84a3a712d 100644 --- a/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java +++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaMulticlassClassificationMetricsExample.java @@ -68,9 +68,7 @@ public class JavaMulticlassClassificationMetricsExample { System.out.println("Confusion matrix: \n" + confusion); // Overall statistics - System.out.println("Precision = " + metrics.precision()); - System.out.println("Recall = " + metrics.recall()); - System.out.println("F1 Score = " + metrics.fMeasure()); + System.out.println("Accuracy = " + metrics.accuracy()); // Stats by labels for (int i = 0; i < metrics.labels().length; i++) { |