spark-instrumented-optimizer/mllib
Ilya Matiach b66be0e490 [SPARK-24103][ML][MLLIB] ML Evaluators should use weight column - added weight column for binary classification 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.

## How was this patch tested?
I added tests to the metrics and evaluators classes.

Closes #17084 from imatiach-msft/ilmat/binary-evalute.

Authored-by: Ilya Matiach <ilmat@microsoft.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-02-25 17:16:51 -06:00
..
benchmarks [SPARK-25489][ML][TEST] Refactor UDTSerializationBenchmark 2018-09-23 13:34:06 -07:00
src [SPARK-24103][ML][MLLIB] ML Evaluators should use weight column - added weight column for binary classification evaluator 2019-02-25 17:16:51 -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