get.yhat: Wrapper Prediction Function

In midr: Learning from Black-Box Models by Maximum Interpretation Decomposition

Wrapper Prediction Function

Description

get.yhat() is a generic function that provides a unified interface for obtaining predictions from various fitted model objects.

Usage

get.yhat(object, newdata, ...)

## Default S3 method:
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'mid'
get.yhat(object, newdata, ...)

## S3 method for class 'lm'
get.yhat(object, newdata, ...)

## S3 method for class 'glm'
get.yhat(object, newdata, ...)

## S3 method for class 'rpart'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'randomForest'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'ranger'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'svm'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'ksvm'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'AccurateGLM'
get.yhat(object, newdata, ...)

## S3 method for class 'glmnet'
get.yhat(object, newdata, ...)

## S3 method for class 'model_fit'
get.yhat(object, newdata, target = -1L, ...)

## S3 method for class 'rpf'
get.yhat(object, newdata, target = -1L, ...)

Arguments

object	a fitted model object.
newdata	a data.frame or matrix.
...	optional arguments passed on to the underlying predict() method for the object's class.
target	an integer or character vector specifying the target levels used for the classification models that return a matrix or data frame of class probabilities. The default, -1, represents the probability of not being the base level.

Details

While many predictive models have a stats::predict() method, the structure and type of their outputs are not uniform. For example, some return a numeric vector, others a matrix of class probabilities, and some a list. This function, get.yhat(), abstracts away this complexity.

For regression models, it returns the numeric prediction in the original scale of the response variable. For classification models, it returns the sum of class probabilities for the classes specified by the target argument.

Furthermore, get.yhat() provides more consistent handling of missing values. While some stats::predict() methods may return a shorter vector by omitting NAs, get.yhat() is designed to return a vector of the same length as newdata, preserving NAs in their original positions.

The design of get.yhat() is strongly influenced by DALEX::yhat().

Value

get.yhat() returns a numeric vector of model predictions for newdata.

See Also

predict.mid

Examples

data(trees, package = "datasets")
model <- glm(Volume ~ ., trees, family = Gamma(log))

# The output of stats::predict() might not be in the scale of the response variable
predict(model, trees[1:5, ])

# get.yhat() returns a numeric vector in the original scale of the response variable
get.yhat(model, trees[1:5, ])
predict(model, trees[1:5, ], type = "response")

midr documentation built on Sept. 11, 2025, 1:07 a.m.