s_LightRuleFit: RuleFit with LightGBM (C, R)
In egenn/rtemis: Machine Learning and Visualization

s_LightRuleFit

R Documentation

RuleFit with LightGBM (C, R)

Description

Train a LightGBM gradient boosting model, extract rules, and fit using LASSO

Usage

s_LightRuleFit(
  x,
  y = NULL,
  x.test = NULL,
  y.test = NULL,
  params = setup.LightRuleFit(),
  lgbm.mod = NULL,
  empirical_risk = TRUE,
  cases_by_rules = NULL,
  save_cases_by_rules = FALSE,
  x.name = NULL,
  y.name = NULL,
  n.cores = rtCores,
  question = NULL,
  print.plot = FALSE,
  plot.fitted = NULL,
  plot.predicted = NULL,
  plot.theme = rtTheme,
  outdir = NULL,
  save.mod = if (!is.null(outdir)) TRUE else FALSE,
  verbose = TRUE,
  trace = 0
)

Arguments

`x`	Numeric vector or matrix / data frame of features i.e. independent variables
`y`	Numeric vector of outcome, i.e. dependent variable
`x.test`	Numeric vector or matrix / data frame of testing set features Columns must correspond to columns in `x`
`y.test`	Numeric vector of testing set outcome
`params`	Training parameters for GBM and LASSO steps, set using setup.LightRuleFit.
`lgbm.mod`	rtMod object created by s_LightGBM. If provided, the gradient boosting step is skipped.
`empirical_risk`	Logical: If TRUE, calculate empirical risk
`cases_by_rules`	Matrix of cases by rules from a previoue rulefit run. If provided, the GBM step is skipped.
`save_cases_by_rules`	Logical: If TRUE, save cases_by_rules to object
`x.name`	Character: Name for feature set
`y.name`	Character: Name for outcome
`n.cores`	Integer: Number of cores to use
`question`	Character: the question you are attempting to answer with this model, in plain language.
`print.plot`	Logical: if TRUE, produce plot using `mplot3` Takes precedence over `plot.fitted` and `plot.predicted`.
`plot.fitted`	Logical: if TRUE, plot True (y) vs Fitted
`plot.predicted`	Logical: if TRUE, plot True (y.test) vs Predicted. Requires `x.test` and `y.test`
`plot.theme`	Character: "zero", "dark", "box", "darkbox"
`outdir`	Path to output directory. If defined, will save Predicted vs. True plot, if available, as well as full model output, if `save.mod` is TRUE
`save.mod`	Logical: If TRUE, save all output to an RDS file in `outdir` `save.mod` is TRUE by default if an `outdir` is defined. If set to TRUE, and no `outdir` is defined, outdir defaults to `paste0("./s.", mod.name)`
`verbose`	Logical: If TRUE, print summary to screen.
`trace`	Integer: Verbosity level