Github user wangmiao1981 commented on a diff in the pull request: https://github.com/apache/spark/pull/15365#discussion_r84988302 --- Diff: R/pkg/R/mllib.R --- @@ -647,6 +654,173 @@ setMethod("predict", signature(object = "KMeansModel"), predict_internal(object, newData) }) +#' Logistic Regression Model +#' +#' Fits an logistic regression model against a Spark DataFrame. It supports "binomial": Binary logistic regression +#' with pivoting; "multinomial": Multinomial logistic (softmax) regression without pivoting, similar to glmnet. +#' Users can print, make predictions on the produced model and save the model to the input path. +#' +#' @param data SparkDataFrame for training +#' @param formula A symbolic description of the model to be fitted. Currently only a few formula +#' operators are supported, including '~', '.', ':', '+', and '-'. +#' @param regParam the regularization parameter. Default is 0.0. +#' @param elasticNetParam the ElasticNet mixing parameter. For alpha = 0, the penalty is an L2 penalty. +#' For alpha = 1, it is an L1 penalty. For 0 < alpha < 1, the penalty is a combination +#' of L1 and L2. Default is 0.0 which is an L2 penalty. +#' @param maxIter maximum iteration number. +#' @param tol convergence tolerance of iterations. +#' @param fitIntercept whether to fit an intercept term. Default is TRUE. +#' @param family the name of family which is a description of the label distribution to be used in the model. +#' Supported options: +#' \itemize{ +#' \item{"auto": Automatically select the family based on the number of classes: +#' If numClasses == 1 || numClasses == 2, set to "binomial". --- End diff -- There is no `numClasses` parameter. The algorithm infers the number of classes. I changed to `number of classes` to avoid confusion.
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