predict.treeda: Predict using new data

In jfukuyama/treeDA: Tree-Based Discriminant Analysis

Description

Given a fitted treeda model, get the predicted classes and projections onto the discriminating axes for new data.

Usage

## S3 method for class 'treeda'
predict(object, newdata, newresponse = NULL, check.consist = TRUE, ...)

Arguments

object	Output from treeda function.
newdata	New predictor matrix in the same format as the predictor argument to treeda. A matrix of predictor variables corresponding to the leaves of the tree and in the same order as the leaves of the tree.
newresponse	New response vector, not required.
check.consist	Check the consistency between the tree and predictor matrix?
...	Not used.

Value

A list containing the projections of the new data onto the discriminating axes (projections), the predicted classes (classes), and the rss (rss, only included if the ground truth for the responses is available).

Examples

data(treeda_example)
out.treeda = treeda(response = treeda_example$response,
    predictors = treeda_example$predictors,
    tree = treeda_example$tree,
    p = 1)
## Here we are predicting on the training data, in general this
## would be done on a held out test set
preds = predict(out.treeda, newdata = treeda_example$predictors,
    newresponse = treeda_example$response)
## make a confusion matrix
table(preds$classes, treeda_example$response)

jfukuyama/treeDA documentation built on May 18, 2021, 8:52 a.m.