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 theobject'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().
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, ])
#> 1 2 3 4 5
#> 2.458590 2.419285 2.415186 2.811365 2.989622
# get.yhat() returns a numeric vector in the original scale of the response variable
get.yhat(model, trees[1:5, ])
#> [1] 11.68832 11.23782 11.19185 16.63260 19.87816
predict(model, trees[1:5, ], type = "response")
#> 1 2 3 4 5
#> 11.68832 11.23782 11.19185 16.63260 19.87816