rtemis (version 0.79)

s.POLYMARS: Multivariate adaptive polynomial spline regression (POLYMARS) [C, R]

Description

Trains a POLYMARS model using polspline::polymars and validates it

Usage

s.POLYMARS(x, y = NULL, x.test = NULL, y.test = NULL,
  x.name = NULL, y.name = NULL,
  grid.resample.rtset = rtset.grid.resample(),
  bag.resample.rtset = NULL, weights = NULL, ipw = TRUE,
  ipw.type = 2, upsample = FALSE, upsample.seed = NULL,
  maxsize = ceiling(min(6 * (nrow(x)^{     1/3 }), nrow(x)/4, 100)),
  classify = NULL, n.cores = rtCores, print.plot = TRUE,
  plot.fitted = NULL, plot.predicted = NULL,
  plot.theme = getOption("rt.fit.theme", "lightgrid"), question = NULL,
  verbose = TRUE, trace = 0, save.mod = FALSE, outdir = NULL, ...)

Arguments

x

Numeric vector or matrix of features, i.e. independent variables

y

Numeric vector of outcome, i.e. dependent variable

x.test

(Optional) Numeric vector or matrix of validation set features must have set of columns as x

y.test

(Optional) Numeric vector of validation set outcomes

...

Additional parameters to pass to polspline::polymars

Value

Object of class rtMod

See Also

elevate for external cross-validation

Other Supervised Learning: s.ADABOOST, s.ADDTREE, s.BART, s.BAYESGLM, s.BRUTO, s.C50, s.CART, s.CTREE, s.DA, s.ET, s.EVTREE, s.GAM.default, s.GAM.formula, s.GAMSEL, s.GAM, s.GBM3, s.GBM, s.GLMNET, s.GLM, s.GLS, s.H2ODL, s.H2OGBM, s.H2ORF, s.IRF, s.KNN, s.LDA, s.LM, s.MARS, s.MLRF, s.MXN, s.NBAYES, s.NLA, s.NLS, s.NW, s.PPR, s.PPTREE, s.QDA, s.QRNN, s.RANGER, s.RFSRC, s.RF, s.SGD, s.SPLS, s.SVM, s.TFN, s.XGBLIN, s.XGB