diff options
Diffstat (limited to 'R/pkg/R/mllib_clustering.R')
| -rw-r--r-- | R/pkg/R/mllib_clustering.R | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/R/pkg/R/mllib_clustering.R b/R/pkg/R/mllib_clustering.R index fb8d9e75ad..fa40f9d0bf 100644 --- a/R/pkg/R/mllib_clustering.R +++ b/R/pkg/R/mllib_clustering.R @@ -98,7 +98,7 @@ setMethod("spark.gaussianMixture", signature(data = "SparkDataFrame", formula = #' @param object a fitted gaussian mixture model. #' @return \code{summary} returns summary of the fitted model, which is a list. #' The list includes the model's \code{lambda} (lambda), \code{mu} (mu), -#' \code{sigma} (sigma), and \code{posterior} (posterior). +#' \code{sigma} (sigma), \code{loglik} (loglik), and \code{posterior} (posterior). #' @aliases spark.gaussianMixture,SparkDataFrame,formula-method #' @rdname spark.gaussianMixture #' @export @@ -112,6 +112,7 @@ setMethod("summary", signature(object = "GaussianMixtureModel"), sigmaList <- callJMethod(jobj, "sigma") k <- callJMethod(jobj, "k") dim <- callJMethod(jobj, "dim") + loglik <- callJMethod(jobj, "logLikelihood") mu <- c() for (i in 1 : k) { start <- (i - 1) * dim + 1 @@ -129,7 +130,7 @@ setMethod("summary", signature(object = "GaussianMixtureModel"), } else { dataFrame(callJMethod(jobj, "posterior")) } - list(lambda = lambda, mu = mu, sigma = sigma, + list(lambda = lambda, mu = mu, sigma = sigma, loglik = loglik, posterior = posterior, is.loaded = is.loaded) }) |