Description Objects from the Class Slots Extends Methods
Class containing the outputs of predict
ing on a test set using a random forest.
Objects can be created by calls of the form new("bigcprediction", ...)
, but most often are generated by predict
.
.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
.
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.
signature(object = "bigcprediction")
: Print prediction results.
signature(object = "bigcprediction")
: Print summary information on prediction results, including test error estimates and the confusion matrix if test labels were supplied during prediction.
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