CART.Rd
Classification And Regression Tree is a simple technique to fit a relationship between numerical variables partitioning the target variable by a range of values of the explanatory variables. This function fits and graphs a cart model with a previous separation of training a testing datasets.
CART(formula, data, p = 0.7, nodes_min = 2, nodes_max = 18, includedata = FALSE, seed = NULL, ...)
formula | a formula of the form y ~ x1 + x2 + ... |
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data | the data frame that contains the variables specified in |
p | the percentage of the training dataset to be obtained randomly. |
nodes_min | Number of minimum nodes. |
nodes_max | Number of maximum nodes. |
includedata | logicals. If TRUE the training and testing datasets are returned. |
seed | a single value, interpreted as an integer, or NULL. The default value is NULL, but for future checks of the model or models generated it is advisable to set a random seed to be able to reproduce it. |
... | further arguments passed to or from other methods. |
A MLA object of subclass CART
## Load a Dataset# NOT RUN { data(EGATUR) CART(GastoTotalD~pais+aloja+motivo,data=EGATUR) # }