Fit a simple, non-informative model
Fit a single mean or largest class model
nullModel(x, ...) ## Default S3 method: nullModel(x = NULL, y, ...) ## S3 method for class 'nullModel' predict(object, newdata = NULL, type = NULL, ...)
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 |
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) |
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.
The output of nullModel is a list of class nullModel
with elements
call |
the function call |
value |
the mean of
|
levels |
when |
pct |
when |
n
|
the number of elements in |
predict.nullModel returns a either a factor or numeric vector
depending on the class of y. All predictions are always the same.
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))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.