Model {agghoo}

R6 class representing a (generic) model.

Description

"Model" class, containing a (generic) learning function, which from data + target [+ params] returns a prediction function X –> y. Parameters for cross-validation are either provided or estimated. Model family can be chosen among "tree", "ppr" and "knn" for now.

Public fields

nmodels

Number of parameters (= number of [predictive] models)

Methods

Public methods

• Model$new()

• Model$get()

• Model$getParam()

• Model$clone()

Method new()

Create a new generic model.

Usage

Model$new(data, target, task, gmodel = NULL, params = NULL)

Arguments

data

Matrix or data.frame

target

Vector of targets (generally numeric or factor)

task

"regression" or "classification"

gmodel

Generic model returning a predictive function; chosen automatically given data and target nature if not provided.

params

List of parameters for cross-validation (each defining a model)

Method get()

Returns the model at index "index", trained on dataHO/targetHO.

Usage

Model$get(dataHO, targetHO, index)

Arguments

dataHO

Matrix or data.frame

targetHO

Vector of targets (generally numeric or factor)

index

Index of the model in 1...nmodels

Method getParam()

Returns the parameter at index "index".

Usage

Model$getParam(index)

Arguments

index

Index of the model in 1...nmodels

Method clone()

The objects of this class are cloneable with this method.

Usage

Model$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.