Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/11136#discussion_r53722399
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -0,0 +1,547 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.regression
+
+import breeze.stats.distributions.{Gaussian => GD}
+
+import org.apache.spark.{Logging, SparkException}
+import org.apache.spark.annotation.{Experimental, Since}
+import org.apache.spark.ml.PredictorParams
+import org.apache.spark.ml.feature.Instance
+import org.apache.spark.ml.optim._
+import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
+import org.apache.spark.ml.util.Identifiable
+import org.apache.spark.mllib.linalg.{BLAS, Vector}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{DataFrame, Row}
+import org.apache.spark.sql.functions._
+
+/**
+ * Params for Generalized Linear Regression.
+ */
+private[regression] trait GeneralizedLinearRegressionParams extends
PredictorParams
+ with HasFitIntercept with HasMaxIter with HasTol with HasRegParam with
HasWeightCol
+ with HasSolver with Logging {
+
+ /**
+ * Param for the name of family which is a description of the error
distribution
+ * to be used in the model.
+ * Supported options: "gaussian", "binomial", "poisson" and "gamma".
+ * @group param
+ */
+ @Since("2.0.0")
+ 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 model",
+
ParamValidators.inArray[String](GeneralizedLinearRegression.supportedFamilies.toArray))
+
+ /** @group getParam */
+ @Since("2.0.0")
+ def getFamily: String = $(family)
+
+ /**
+ * Param for the name of the model link function.
+ * Supported options: "identity", "log", "inverse", "logit", "probit",
"cloglog" and "sqrt".
+ * @group param
+ */
+ @Since("2.0.0")
+ final val link: Param[String] = new Param(this, "link", "the name of the
model link function",
+
ParamValidators.inArray[String](GeneralizedLinearRegression.supportedLinks.toArray))
+
+ /** @group getParam */
+ @Since("2.0.0")
+ def getLink: String = $(link)
+
+ @Since("2.0.0")
+ override def validateParams(): Unit = {
+ if (isDefined(link)) {
+
require(GeneralizedLinearRegression.supportedFamilyLinkPairs.contains($(family)
-> $(link)),
+ s"Generalized Linear Regression with ${$(family)} family does not
support ${$(link)} " +
+ s"link function.")
+ }
+ }
+}
+
+/**
+ * :: Experimental ::
+ *
+ * Fit a Generalized Linear Model
([[https://en.wikipedia.org/wiki/Generalized_linear_model]])
+ * specified by giving a symbolic description of the linear predictor and
+ * a description of the error distribution.
+ */
+@Experimental
+@Since("2.0.0")
+class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0")
override val uid: String)
+ extends Regressor[Vector, GeneralizedLinearRegression,
GeneralizedLinearRegressionModel]
+ with GeneralizedLinearRegressionParams with Logging {
+
+ @Since("2.0.0")
+ def this() = this(Identifiable.randomUID("genLinReg"))
+
+ /**
+ * Set the name of family which is a description of the error
distribution
--- End diff --
* `Set` -> `Sets`
* I don't think it is necessary to repeat the param doc. Maybe we can
simply say `Sets the value of param [[family]].`
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