Generalized Linear Models (R-compliant)

Fits a generalized linear model, similarly to R's glm().

Usage

# S4 method for class 'formula,ANY,SparkDataFrame'
glm(
  formula,
  family = gaussian,
  data,
  epsilon = 1e-06,
  maxit = 25,
  weightCol = NULL,
  var.power = 0,
  link.power = 1 - var.power,
  stringIndexerOrderType = c("frequencyDesc", "frequencyAsc", "alphabetDesc",
    "alphabetAsc"),
  offsetCol = NULL
)

Arguments

formula

a symbolic description of the model to be fitted. Currently only a few formula operators are supported, including '~', '.', ':', '+', and '-'.

family

a description of the error distribution and link function to be used in the model. This can be a character string naming a family function, a family function or the result of a call to a family function. Refer R family at https://stat.ethz.ch/R-manual/R-devel/library/stats/html/family.html. Currently these families are supported: binomial, gaussian, poisson, Gamma, and tweedie.

data

a SparkDataFrame or R's glm data for training.

epsilon

positive convergence tolerance of iterations.

maxit

integer giving the maximal number of IRLS iterations.

weightCol

the weight column name. If this is not set or NULL, we treat all instance weights as 1.0.

var.power

the index of the power variance function in the Tweedie family.

link.power

the index of the power link function in the Tweedie family.

stringIndexerOrderType

how to order categories of a string feature column. This is used to decide the base level of a string feature as the last category after ordering is dropped when encoding strings. Supported options are "frequencyDesc", "frequencyAsc", "alphabetDesc", and "alphabetAsc". The default value is "frequencyDesc". When the ordering is set to "alphabetDesc", this drops the same category as R when encoding strings.

offsetCol

the offset column name. If this is not set or empty, we treat all instance offsets as 0.0. The feature specified as offset has a constant coefficient of 1.0.

Value

glm returns a fitted generalized linear model.

Note

glm since 1.5.0

See also

spark.glm

Examples

if (FALSE) { # \dontrun{
sparkR.session()
t <- as.data.frame(Titanic)
df <- createDataFrame(t)
model <- glm(Freq ~ Sex + Age, df, family = "gaussian")
summary(model)
} # }