From 3dcad9fab17297f9966026f29fefb5c726965a13 Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Sat, 21 Jan 2017 21:15:57 -0800
Subject: [PATCH] [SPARK-19155][ML] MLlib GeneralizedLinearRegression family
and link should case insensitive
## What changes were proposed in this pull request?
MLlib ```GeneralizedLinearRegression``` ```family``` and ```link``` should be case insensitive. This is consistent with some other MLlib params such as [```featureSubsetStrategy```](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala#L415).
## How was this patch tested?
Update corresponding tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #16516 from yanboliang/spark-19133.
---
.../spark/ml/regression/GeneralizedLinearRegression.scala | 8 ++++----
.../ml/regression/GeneralizedLinearRegressionSuite.scala | 4 ++--
2 files changed, 6 insertions(+), 6 deletions(-)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
index a32302bf5d..116f0f6507 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
@@ -57,7 +57,7 @@ private[regression] trait GeneralizedLinearRegressionBase extends PredictorParam
final val family: Param[String] = new Param(this, "family",
"The name of family which is a description of the error distribution to be used in the " +
s"model. Supported options: ${supportedFamilyNames.mkString(", ")}.",
- ParamValidators.inArray[String](supportedFamilyNames.toArray))
+ (value: String) => supportedFamilyNames.contains(value.toLowerCase))
/** @group getParam */
@Since("2.0.0")
@@ -74,7 +74,7 @@ private[regression] trait GeneralizedLinearRegressionBase extends PredictorParam
final val link: Param[String] = new Param(this, "link", "The name of link function " +
"which provides the relationship between the linear predictor and the mean of the " +
s"distribution function. Supported options: ${supportedLinkNames.mkString(", ")}",
- ParamValidators.inArray[String](supportedLinkNames.toArray))
+ (value: String) => supportedLinkNames.contains(value.toLowerCase))
/** @group getParam */
@Since("2.0.0")
@@ -414,7 +414,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
* @param name family name: "gaussian", "binomial", "poisson" or "gamma".
*/
def fromName(name: String): Family = {
- name match {
+ name.toLowerCase match {
case Gaussian.name => Gaussian
case Binomial.name => Binomial
case Poisson.name => Poisson
@@ -626,7 +626,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
* "inverse", "probit", "cloglog" or "sqrt".
*/
def fromName(name: String): Link = {
- name match {
+ name.toLowerCase match {
case Identity.name => Identity
case Logit.name => Logit
case Log.name => Log
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
index ed24c1e16a..9f3d643c2b 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
@@ -553,7 +553,7 @@ class GeneralizedLinearRegressionSuite
for ((link, dataset) <- Seq(("inverse", datasetGammaInverse),
("identity", datasetGammaIdentity), ("log", datasetGammaLog))) {
for (fitIntercept <- Seq(false, true)) {
- val trainer = new GeneralizedLinearRegression().setFamily("gamma").setLink(link)
+ val trainer = new GeneralizedLinearRegression().setFamily("Gamma").setLink(link)
.setFitIntercept(fitIntercept).setLinkPredictionCol("linkPrediction")
val model = trainer.fit(dataset)
val actual = Vectors.dense(model.intercept, model.coefficients(0), model.coefficients(1))
@@ -990,7 +990,7 @@ class GeneralizedLinearRegressionSuite
-0.6344390 0.3172195 0.2114797 -0.1586097
*/
val trainer = new GeneralizedLinearRegression()
- .setFamily("gamma")
+ .setFamily("Gamma")
.setWeightCol("weight")
val model = trainer.fit(datasetWithWeight)
--
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