nullModel
Fit a simple, non-informative model
Fit a single mean or largest class model
- Keywords
- models
Usage
nullModel(x, ...)# S3 method for default
nullModel(x = NULL, y, ...)
# S3 method for nullModel
predict(object, newdata = NULL, type = NULL, ...)
Arguments
- x
An optional matrix or data frame of predictors. These values are not used in the model fit
- …
Optional arguments (not yet used)
- y
A numeric vector (for regression) or factor (for classification) of outcomes
- object
An object of class
nullModel- newdata
A matrix or data frame of predictors (only used to determine the number of predictions to return)
- type
Either "raw" (for regression), "class" or "prob" (for classification)
Details
nullModel emulates other model building functions, but returns the
simplest model possible given a training set: a single mean for numeric
outcomes and the most prevalent class for factor outcomes. When class
probabilities are requested, the percentage of the training set samples with
the most prevalent class is returned.
Value
The output of nullModel is a list of class nullModel
with elements
the function call
the mean of
y or the most prevalent class
when y is a
factor, a vector of levels. NULL otherwise
when y
is a factor, a data frame with a column for each class (NULL
otherwise). The column for the most prevalent class has the proportion of
the training samples with that class (the other columns are zero).
the number of elements in y
predict.nullModel returns a either a factor or numeric vector depending on the class of y. All predictions are always the same.
Examples
# NOT RUN {
outcome <- factor(sample(letters[1:2],
size = 100,
prob = c(.1, .9),
replace = TRUE))
useless <- nullModel(y = outcome)
useless
predict(useless, matrix(NA, nrow = 10))
# }