blip.scorer {r.blip}

Parent set exploration

Description

Generates the cache of parent sets from a given data source

Usage

blip.scorer(dat, method = "is", indeg = 6, time = 3600,
  scorefunction = "bic", alpha = 1, cores = 1, verbose = 0)

Arguments

dat

dataframe from which to learn the parent sets.(required)

method

Method to be used. Possible values: "is" (independence selection), "sq" (sequential selection). (default: is)

indeg

Maximum number of parents (default: 6)

time

Maximum Execution time (default: 3600)

scorefunction

Chosen score function. Possible choices: BIC, BDeu (default: bic)

alpha

(if BDeu is chosen) equivalent sample size parameter (default: 1.0)

cores

Number of machine cores to use. If 0, all are used. (default: 1)

verbose

Verbose level (default: 0)

Details

Usually the first step in the learning of a Bayesian network.

The input data is required to be complete and discrete. Accordingly missing values in the input data.frame will be ignored, and all numeric values will be converted to integers.

Value

Cache of parent sets

Examples

jkl <- blip.scorer(child, time=3)