Summarizes a pptr model.
summary.pptr.RdSummarizes a pptr model.
Usage
# S3 method for class 'pptr'
summary(object, ...)Examples
model <- pptr(Type ~ ., data = iris)
summary(model)
#>
#> Project-Pursuit Oblique Decision Tree
#>
#> pp method: LDA (lambda=0)
#> dr method: All variables
#> sr method: Mean of means
#>
#>
#> Data Summary:
#> observations: 150
#> features: 4
#> groups: 3
#> group names: setosa, versicolor, virginica
#> formula: Type ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width - 1
#>
#> Confusion Matrix:
#>
#> Predicted
#> Actual setosa versicolor virginica
#> setosa 50 0 0
#> versicolor 0 48 2
#> virginica 0 1 49
#>
#> Training error: 2%
#>
#> Variable Importance:
#>
#> Variable σ Projection
#> 1 Petal.Length 1.7652982 0.10064526
#> 2 Petal.Width 0.7622377 0.06144172
#> 3 Sepal.Length 0.8280661 0.02164980
#> 4 Sepal.Width 0.4358663 0.02155388
#>
#> Note: Variable importance was calculated using scaled coefficients (|a_j| * σ_j).
#> Variable contributions can only be theoretically interpreted as such
#> if the model was trained on scaled data. Scaling also changes the
#> projection-pursuit optimization, which may affect the resulting tree.
#>