Trains a GAM using mgcv::gam and validates it.
Input will be used to create a formula of the form:
$$y = s(x_{1}, k = gam.k) + s(x_{2}, k = gam.k) + ... + s(x_{n}, k = gam.k)$$
s.GAM(x, ...)Numeric vector or matrix / data frame of features i.e. independent variables
Additional arguments to be passed to mgcv::gam
Factors to be included as covariates in model building
Factors to be included as covariates in model validation
Integer. Number of bases for smoothing spline
Only s.GAM.default is actively maintained at the moment
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.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.POLYMARS, 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