Description Usage Arguments Details Value Author(s) References See Also Examples

Returns predictions from a fitted `oblique.tree`

object.

1 2 3 4 5 6 7 8 |

`object` |
Fitted model object of class |

`newdata` |
Data frame containing the values at which predictions are required. The predictors referred to in the right side of |

`type` |
Character string denoting how predictions are to be returned, i.e. class probabilities (default), a tree object, class predictions or predictions to leaf nodes. |

`eps` |
A lower bound for the probabilities, used if events of predicted probability zero occur in |

`update.tree.predictions` |
Logical vector denoting whether tree predictions ( |

`...` |
Further arguments passed to or from other methods. |

This function is a method for the generic function `predict()`

for objects of class `c("oblique.tree","tree")`

. It can be invoked by calling `predict(x)`

for an object `x`

of the appropriate class or directly by calling `predict.oblique.tree(x)`

regardless of the class of the object.

If `type = "vector"`

:
a matrix of predicted class probabilities is returned. This object is obtained by dropping observations down `object`

.

If `type = "tree"`

:
an object of class `c("oblique.tree","tree")`

is returned with new values for `frame$n`

and `frame$dev`

.

If `type = "class"`

:
a factor of the predicted classes (that with highest posterior probability, with ties split randomly).

If `type = "where"`

:
the nodes the cases reach.

A. Truong

Truong. A (2009) *Fast Growing and Interpretable Oblique Trees via Probabilistic Models*

Ripley, B. D. (1996). *Pattern Recognition and Neural Networks.* Cambridge University Press, Cambridge. Chapter 7.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
#grow an oblique tree to the Pima Indian dataset
data(Pima.tr, package = "MASS")
ob.tree <- oblique.tree(formula = type~.,
data = Pima.tr,
oblique.splits = "on")
plot(ob.tree);text(ob.tree);title(main="Oblique Tree")
#predictions to in-sample data
#class probabilities for each observation
predict(ob.tree,type="vector")
#the tree itself
predict(ob.tree,type="tree")
#class predictions for each observation
predict(ob.tree,type="class")
#the leaf where each observation falls
predict(ob.tree,type="where")
#predictions to out-of-sample data
data(Pima.te, package = "MASS")
#class probabilities for each observation
predict(ob.tree,newdata=Pima.te,type="vector")
#the tree itself
predict(ob.tree,newdata=Pima.te,type="tree")
#class predictions for each observation
predict(ob.tree,newdata=Pima.te,type="class")
#the leaf where each observation falls
predict(ob.tree,newdata=Pima.te,type="where")
``` |

oblique.tree documentation built on April 15, 2017, 4:38 a.m.

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