classPrototypes | R Documentation |
For each class the most typical instances are returned based on the highest predicted probability for each class.
classPrototypes(model, dataset, noPrototypes=10)
model |
a |
dataset |
a dataset from which to get prototypes. |
noPrototypes |
number of instances of each class to return |
The function uses predict.CoreModel(model, dataset)
for prediction of the dataset
with
model
. Based on the returned probabilities, it selects the noPrototypes
instances with highest probabilities for each class to be
typical representatives of that class, i.e., prototypes. The prototypes can be
visualized by calling e.g.,
plot(model, dataset, rfGraphType="prototypes", noPrototypes = 10)
.
A list with the most typical noPrototypes
instances is returned. The list has the following attributes.
prototypes |
vector with indexes of the most typical instances |
clustering |
vector with class assignments for typical instances in vector |
levels |
the names of the class values. |
John Adeyanju Alao (as a part of his BSc thesis) and Marko Robnik-Sikonja (thesis supervisor)
Leo Breiman: Random Forests. Machine Learning Journal, 45:5-32, 2001
predict.CoreModel
,
plot.CoreModel
.
dataset <- iris md <- CoreModel(Species ~ ., dataset, model="rf", rfNoTrees=30,maxThreads=1) typical <- classPrototypes(md, dataset, 10) destroyModels(md) # clean up
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