Github user yanboliang commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16344#discussion_r93776723
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
 ---
    @@ -397,46 +434,118 @@ object GeneralizedLinearRegression extends 
DefaultParamsReadable[GeneralizedLine
     
         /** Trim the fitted value so that it will be in valid range. */
         def project(mu: Double): Double = mu
    +
       }
     
       private[regression] object Family {
     
         /**
    -     * Gets the [[Family]] object from its name.
    +     * Gets the [[Family]] object based on family and variancePower.
    +     * 1) retrieve object based on family name
    +     * 2) if family name is tweedie, retrieve object based on variancePower
          *
    -     * @param name family name: "gaussian", "binomial", "poisson" or 
"gamma".
    +     * @param model a GenerealizedLinearRegressionBase object
          */
    -    def fromName(name: String): Family = {
    -      name match {
    -        case Gaussian.name => Gaussian
    -        case Binomial.name => Binomial
    -        case Poisson.name => Poisson
    -        case Gamma.name => Gamma
    +    def fromModel(model: GeneralizedLinearRegressionBase): Family = {
    +      model.getFamily match {
    +        case "gaussian" => Gaussian
    +        case "binomial" => Binomial
    +        case "poisson" => Poisson
    +        case "gamma" => Gamma
    +        case "tweedie" =>
    +          model.getVariancePower match {
    +            case 0.0 => Gaussian
    +            case 1.0 => Poisson
    +            case 2.0 => Gamma
    +            case default => new TweedieFamily(default)
    +          }
           }
         }
       }
     
       /**
    -   * Gaussian exponential family distribution.
    -   * The default link for the Gaussian family is the identity link.
    -   */
    -  private[regression] object Gaussian extends Family("gaussian") {
    +    * Tweedie exponential family distribution.
    +    * This includes the special cases of Gaussian, Poisson and Gamma.
    +    */
    +  private[regression] class TweedieFamily(private val variancePower: 
Double)
    +    extends Family("tweedie") {
    +
    +    /*
    +      The canonical link is 1 - variancePower. Except for the special 
cases of Gaussian,
    +      Poisson and Gamma, the canonical link is rarely used. Set Log as the 
default link.
    +    */
    +    override val defaultLink: Link = Log
     
    -    val defaultLink: Link = Identity
    +    override def initialize(y: Double, weight: Double): Double = {
    +      if (variancePower >= 1.0 && variancePower < 2.0) {
    +        require(y >= 0.0, s"The response variable of the specified 
distribution " +
    --- End diff --
    
    ```The response variable of $name family ```


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