spark-instrumented-optimizer/mllib
Ilya Matiach 570b8f3d45 [SPARK-24102][ML][MLLIB] ML Evaluators should use weight column - added weight column for regression evaluator
## What changes were proposed in this pull request?

The evaluators BinaryClassificationEvaluator, RegressionEvaluator, and MulticlassClassificationEvaluator and the corresponding metrics classes BinaryClassificationMetrics, RegressionMetrics and MulticlassMetrics should use sample weight data.

I've closed the PR: https://github.com/apache/spark/pull/16557
 as recommended in favor of creating three pull requests, one for each of the evaluators (binary/regression/multiclass) to make it easier to review/update.

The updates to the regression metrics were based on (and updated with new changes based on comments):
https://issues.apache.org/jira/browse/SPARK-11520
 ("RegressionMetrics should support instance weights")
 but the pull request was closed as the changes were never checked in.

## How was this patch tested?

I added tests to the metrics class.

Closes #17085 from imatiach-msft/ilmat/regression-evaluate.

Authored-by: Ilya Matiach <ilmat@microsoft.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2018-12-12 10:06:41 -06:00
..
benchmarks [SPARK-25489][ML][TEST] Refactor UDTSerializationBenchmark 2018-09-23 13:34:06 -07:00
src [SPARK-24102][ML][MLLIB] ML Evaluators should use weight column - added weight column for regression evaluator 2018-12-12 10:06:41 -06:00
pom.xml [SPARK-25956] Make Scala 2.12 as default Scala version in Spark 3.0 2018-11-14 16:22:23 -08:00