Convert a CHAID tree to a partykit constparty

Converts a fitted "chaid" object to a partykit::constparty object so that the 'partykit' toolbox (plot(), print(), nodeapply(), 'ggparty', ...) can be used. Binned continuous predictors are represented as ordered factors of the bin interval labels, and all splits become index-type partykit::partysplit objects, so missing values ("<NA>" level) are routed explicitly and split rules display the interval labels.

Usage

chaid_as_party(x, data, weights = NULL, freq = NULL, ...)

# S3 method for class 'chaid'
as.party(obj, data, weights = NULL, freq = NULL, ...)

Arguments

x, obj

A fitted "chaid" object returned by chaid().

data

The data frame used to fit the tree (the chaid object does not store the data).

weights, freq

The case and frequency weights used in the fit, if any. Required to reproduce the case exclusions of the fit.

...

Ignored.

Value

A partykit::constparty object.

Details

The returned object is intended for visualisation and structural inspection. For predictions on new data use predict.chaid(); the predict() method of the party object expects the converted data representation, not the original one.

See also

chaid(), predict.chaid()

Examples

fit <- chaid(Species ~ ., data = iris,
             control = chaid_control(min_parent = 30, min_child = 10))
pt <- chaid_as_party(fit, data = iris)
print(pt)
#> 
#> Model formula:
#> Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width
#> 
#> Fitted party:
#> [1] root
#> |   [2] Petal.Length <= 1.3, (1.3, 1.4], (1.4, 1.6]: setosa (n = 44, err = 0.0%)
#> |   [3] Petal.Length in (1.6, 3.8]: versicolor (n = 14, err = 42.9%)
#> |   [4] Petal.Length in (3.8, 4.3], (4.3, 4.6]: versicolor (n = 32, err = 3.1%)
#> |   [5] Petal.Length in (4.6, 4.9]: versicolor (n = 14, err = 35.7%)
#> |   [6] Petal.Length in (4.9, 5.3]: virginica (n = 16, err = 12.5%)
#> |   [7] Petal.Length in (5.3, 5.7], (5.7, 6.9]: virginica (n = 30, err = 0.0%)
#> 
#> Number of inner nodes:    1
#> Number of terminal nodes: 6