bigcprediction.class: Random Forest Predictions

Description Objects from the Class Slots Extends Methods

Description

Class containing the outputs of predicting on a test set using a random forest.

Objects from the Class

Objects can be created by calls of the form new("bigcprediction", ...), but most often are generated by predict.

Slots

.Data:

Object of class "integer". The predicted class for each test example.

ntest:

Object of class "integer". The number of test examples used for prediction.

testlabelled:

Object of class "logical". Whether the test examples were labelled. If TRUE, then error estimates and the confusion matrix are available.

ntrees:

Object of class "integer". Number of trees in the random forest.

testytable:

Object of class "table". Counts of test examples in each class, if test examples were labelled. Otherwise, NULL.

testvotes:

Object of class "matrix". Weighted class votes for each test example. The prediction for each example is the class that received the highest total vote.

testclserr:

Object of class "numeric". Prediction error for each class, if test examples were labelled. Otherwise, NULL.

testerr:

Object of class "numeric". Total prediction error for all classes, if test examples were labelled. Otherwise, NULL.

testconfusion:

Object of class "table". The confusion matrix for the test set, if test examples were labelled. Otherwise, NULL.

Extends

Class "integer", from data part.
Class "numeric", by class "integer", distance 2.
Class "vector", by class "integer", distance 2.
Class "data.frameRowLabels", by class "integer", distance 2.

Methods

show

signature(object = "bigcprediction"): Print prediction results.

summary

signature(object = "bigcprediction"): Print summary information on prediction results, including test error estimates and the confusion matrix if test labels were supplied during prediction.


aloysius-lim/bigrf documentation built on May 11, 2019, 11:20 p.m.