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-rw-r--r--mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala8
-rw-r--r--mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala2
-rw-r--r--mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala4
-rw-r--r--mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala2
4 files changed, 10 insertions, 6 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index d13109d9da..f136bcee9c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -74,7 +74,7 @@ class LogisticRegression(override val uid: String)
setDefault(elasticNetParam -> 0.0)
/**
- * Set the maximal number of iterations.
+ * Set the maximum number of iterations.
* Default is 100.
* @group setParam
*/
@@ -90,7 +90,11 @@ class LogisticRegression(override val uid: String)
def setTol(value: Double): this.type = set(tol, value)
setDefault(tol -> 1E-6)
- /** @group setParam */
+ /**
+ * Whether to fit an intercept term.
+ * Default is true.
+ * @group setParam
+ * */
def setFitIntercept(value: Boolean): this.type = set(fitIntercept, value)
setDefault(fitIntercept -> true)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
index 1ffb5eddc3..8ffbcf0d8b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
@@ -33,7 +33,7 @@ private[shared] object SharedParamsCodeGen {
val params = Seq(
ParamDesc[Double]("regParam", "regularization parameter (>= 0)",
isValid = "ParamValidators.gtEq(0)"),
- ParamDesc[Int]("maxIter", "max number of iterations (>= 0)",
+ ParamDesc[Int]("maxIter", "maximum number of iterations (>= 0)",
isValid = "ParamValidators.gtEq(0)"),
ParamDesc[String]("featuresCol", "features column name", Some("\"features\"")),
ParamDesc[String]("labelCol", "label column name", Some("\"label\"")),
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
index ed08417bd4..a0c8ccdac9 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
@@ -45,10 +45,10 @@ private[ml] trait HasRegParam extends Params {
private[ml] trait HasMaxIter extends Params {
/**
- * Param for max number of iterations (>= 0).
+ * Param for maximum number of iterations (>= 0).
* @group param
*/
- final val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations (>= 0)", ParamValidators.gtEq(0))
+ final val maxIter: IntParam = new IntParam(this, "maxIter", "maximum number of iterations (>= 0)", ParamValidators.gtEq(0))
/** @group getParam */
final def getMaxIter: Int = $(maxIter)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index fe2a71a331..70cd8e9e87 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -83,7 +83,7 @@ class LinearRegression(override val uid: String)
setDefault(elasticNetParam -> 0.0)
/**
- * Set the maximal number of iterations.
+ * Set the maximum number of iterations.
* Default is 100.
* @group setParam
*/