RecursivePartitioningTreeClustering: End function to evaluate (using RF) predictor candidates on...
In thecomeonman/CURD: Implementation of the CURD algorithm for clustering

View source: R/RecursivePartitioningTreeClustering.R

Recursive partitioning This is the wrapper function that recursively partitions the dataset to form a tree-based clustering solution. The boundary conditions are: - Less than a prespecified number of points at a node - No more node candidates - No distinct feature values in any of the node candidates - Tree depth has reached a maximum

RecursivePartitioningTreeClustering(dtDataset, vRows, vNodeCandidates,
  vPredictorFeatures, vKeyFeatures, dtFeatureChunking, lTree, nTreeDepth,
  nMinRows = 1, nMaxTreeDepth = Inf, cClassifier = "RF",
  bKeepFeatureInMixAfterSplit = FALSE,
  bKeepFeatureInPredAfterSplit = TRUE,
  bUseOptimalChunkPerformance = TRUE)