s_GAM: Generalized Additive Model (GAM) C, R

In egenn/rtemis: Machine Learning and Visualization

Generalized Additive Model (GAM) C, R

Description

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)

Usage

s_GAM(x, ...)

Arguments

x	Numeric vector or matrix / data frame of features i.e. independent variables
...	Additional arguments to be passed to mgcv::gam

Details

Only s_GAM.default is actively maintained at the moment

Value

rtMod

Author(s)

E.D. Gennatas

See Also

train_cv for external cross-validation

Other Supervised Learning: s_AdaBoost(), s_AddTree(), s_BART(), s_BRUTO(), s_BayesGLM(), s_C50(), s_CART(), s_CTree(), s_EVTree(), s_GAM.default(), s_GAM.formula(), s_GBM(), s_GLM(), s_GLMNET(), s_GLMTree(), s_GLS(), s_H2ODL(), s_H2OGBM(), s_H2ORF(), s_HAL(), s_KNN(), s_LDA(), s_LM(), s_LMTree(), s_LightCART(), s_LightGBM(), s_MARS(), s_MLRF(), s_NBayes(), s_NLA(), s_NLS(), s_NW(), s_PPR(), s_PolyMARS(), s_QDA(), s_QRNN(), s_RF(), s_RFSRC(), s_Ranger(), s_SDA(), s_SGD(), s_SPLS(), s_SVM(), s_TFN(), s_XGBoost(), s_XRF()

egenn/rtemis documentation built on May 4, 2024, 7:40 p.m.