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MachineShop (version 3.5.0)

models: Models

Description

Model constructor functions supplied by MachineShop are summarized in the table below according to the types of response variables with which each can be used.

FunctionCategoricalContinuousSurvival
AdaBagModelf
AdaBoostModelf
BARTModelfnS
BARTMachineModelbn
BlackBoostModelbnS
C50Modelf
CForestModelfnS
CoxModelS
CoxStepAICModelS
EarthModelfn
FDAModelf
GAMBoostModelbnS
GBMModelfnS
GLMBoostModelbnS
GLMModelfm,n
GLMStepAICModelbn
GLMNetModelfm,nS
KNNModelf,on
LARSModeln
LDAModelf
LMModelfm,n
MDAModelf
NaiveBayesModelf
NNetModelfn
ParsnipModelfm,nS
PDAModelf
PLSModelfn
POLRModelo
QDAModelf
RandomForestModelfn
RangerModelfnS
RFSRCModelfm,nS
RFSRCFastModelfm,nS
RPartModelfnS
SurvRegModelS
SurvRegStepAICModelS
SVMModelfn
SVMANOVAModelfn
SVMBesselModelfn
SVMLaplaceModelfn
SVMLinearModelfn
SVMPolyModelfn
SVMRadialModelfn
SVMSplineModelfn
SVMTanhModelfn
TreeModelfn
XGBModelfnS
XGBDARTModelfnS
XGBLinearModelfnS
XGBTreeModelfnS

Categorical: b = binary, f = factor, o = ordered
Continuous: m = matrix, n = numeric
Survival: S = Surv

Models may be combined, tuned, or selected with the following meta-model functions.

ModelSpecificationModel specification
StackedModelStacked regression
SuperModelSuper learner
SelectedModelModel selection from a candidate set
TunedModelModel tuning over a parameter grid

Arguments

See Also

modelinfo, fit, resample