RFModel {CaseBasedReasoning}

RandomForest Model for Searching Similar Cases

Description

RandomForest Model for Searching Similar Cases

RandomForest Model for Searching Similar Cases

Details

This class uses the proximity or depth matrix of the RandomForest algorithm as a similarity matrix of training and query observations. By default all cases with at least one missing values are dropped from learning, calculating the distance matrix and searching for similar cases.

Super class

CaseBasedReasoning::CBRBase -> RFModel

Public fields

model

the statistical model

model_params

model arguments

dist_method

Distance method

Methods

Public methods

• RFModel$print()

• RFModel$new()

• RFModel$fit()

• RFModel$set_distance_method()

• RFModel$clone()

Inherited methods

• CaseBasedReasoning::CBRBase$calc_distance_matrix()
• CaseBasedReasoning::CBRBase$get_similar_cases()

Method print()

Prints information of the initialized object

Usage

RFModel$print()

Method new()

Initialize a RandomForest object for searching similar cases.

Usage

RFModel$new(formula, data, ...)

Arguments

formula

Object of class formula or character describing the model fit.

data

Training data of class data.frame

...

ranger RandomForest arguments

Method fit()

Fit the RandomForest

Usage

RFModel$fit()

Arguments

x

Training data of class data.frame

Method set_distance_method()

Set the distance method. Available are Proximity and Depth

Usage

RFModel$set_distance_method(method = "Depth")

Arguments

method

Distance calculation method (default: Proximity)

Method clone()

The objects of this class are cloneable with this method.

Usage

RFModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Englund and Verikas. A novel approach to estimate proximity in a random forest: An exploratory study.