nullModel function

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, ...)

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)

Returns

The output of nullModel is a list of class nullModel

with elements - call: the function call - value: the mean of y or the most prevalent class - levels: when y is a factor, a vector of levels. NULL otherwise - pct: 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 of y. All predictions are always the same.

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.

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))