wekakt / com.github.stevenlang.wekakt.extensions / weka.clusterers.Clusterer / evaluate
fun Clusterer.evaluate(trainData: Instances, testData: Instances): ClusterEvaluation
Create a clusterer evaluation. Builds the clusterer and tests it on the given test set.
val em: Clusterer = EM()
val iris: Instances = getIris()
val (train, test) = iris.split(33.0)
// Evaluate hold-out
val eval: ClustererEvaluation = em.evaluate(trainData = train, testData = test)
trainData - Training data
testData - Testing data
Return Clusterer evaluation
fun Clusterer.evaluate(data: Instances, testPercentage: Double): ClusterEvaluation
Create a clusterer evaluation. Split input data into train and test set. Builds the clusterer on the training set and tests it on the test set.
val em: Clusterer = EM()
val iris: Instances = getIris()
// Evaluate hold-out
val eval: ClustererEvaluation = em.evaluate(data = iris, testPercentage = 33.0)
data - Input dataset
testPercentage - Testing data split percentage
Return Clusterer evaluation