PredictorCaret: PredictorCaret

In fmeffects: Model-Agnostic Interpretations with Forward Marginal Effects

PredictorCaret

Description

This task specializes Predictor for caret regression models. The model is assumed to be a c("train", "train.formula").

It is recommended to use makePredictor() for construction of Predictor objects.

Super class

fmeffects::Predictor -> PredictorCaret

Methods

Public methods

• PredictorCaret$new()

• PredictorCaret$predict()

• PredictorCaret$clone()

---

Method new()

Create a new PredictorCaret object.

Usage

PredictorCaret$new(model, data)

Arguments

model

⁠train, train.formula⁠ object.

data

The data used for computing FMEs, must be data.frame or data.table.

---

Method predict()

Predicts on an observation "newdata".

Usage

PredictorCaret$predict(newdata)

Arguments

newdata

The feature vector for which the target should be predicted.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PredictorCaret$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

fmeffects documentation built on June 22, 2024, 9:32 a.m.