nullModel
From caret v5.09-012
by Max Kuhn
Fit a simple, non-informative model
Fit a single mean or largest class model
- Keywords
- models
Usage
nullModel(x, ...)## S3 method for class 'default':
nullModel(x = NULL, y, ...)
## S3 method for class '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
- y
- A numeric vector (for regression) or factor (for classification) of outcomes
- ...
- Optional arguments (not yet used)
- 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 classnullModel
with elements call the function call value the mean of y
or the most prevalent classlevels when y
is a factor, a vector of levels.NULL
otherwisepct 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).n the number of elements in y
predict.nullModel
returns a either a factor or numeric vector depending on the class ofy
. All predictions are always the same.
Examples
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))
Community examples
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