Learning Hierarchical Clustering Algorithms
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘LearnClust’ version 1.1
Help Pages
| agglomerativeHC | To execute agglomerative hierarchical clusterization algorithm by distance and approach. |
| agglomerativeHC.details | To explain agglomerative hierarchical clusterization algorithm by distance and approach. |
| canberradistance | To calculate the Canberra distance. |
| canberradistance.details | To show the formula and to return the Canberra distance. |
| canberradistanceW | To calculate the Canberra distance applying weights. |
| canberradistanceW.details | To calculate the Canberra distance applying weights . |
| chebyshevDistance | To calculate the Chebyshev distance. |
| chebyshevDistance.details | To show the formula of the Chebyshev distance. |
| chebyshevDistanceW | To calculate the Chebyshev distance applying weights. |
| chebyshevDistanceW.details | To calculate the Chebyshev distance applying weights. |
| clusterDistance | To calculate the distance between clusters. |
| clusterDistance.details | To explain how to calculate the distance between clusters. |
| clusterDistanceByApproach | To calculate the distance by approach option. |
| clusterDistanceByApproach.details | To explain how to calculate the distance by approach option. |
| complementaryClusters | To check if two clusters are complementary |
| complementaryClusters.details | To explain how and why two clusters are complementary. |
| correlationHC | To execute hierarchical correlation algorithm. |
| correlationHC.details | To explain how hierarchical correlation algorithm works. |
| distances | To calculate distances applying weights. |
| distances.details | To calculate distances applying weights. |
| divisiveHC | To execute divisive hierarchical clusterization algorithm by distance and approach. |
| divisiveHC.details | To explain the divisive hierarchical clusterization algorithm by distance and approach. |
| edistance | To calculate the Euclidean distance. |
| edistance.details | To show the Euclidean distance formula. |
| edistanceW | To calculate the Euclidean distance applying weights. |
| edistanceW.details | To calculate the Euclidean distance applying weights. |
| getCluster | To get the clusters with minimal distance. |
| getCluster.details | To explain how to get the clusters with minimal distance. |
| getClusterDivisive | To get the clusters with maximal distance. |
| getClusterDivisive.details | To explain how to get the clusters with maximal distance. |
| initClusters | To initialize clusters for the divisive algorithm. |
| initClusters.details | To explain how to initialize clusters for the divisive algorithm. |
| initData | To initialize data, hierarchical correlation algorithm. |
| initData.details | To initialize data, hierarchical correlation algorithm. |
| initImages | To display an image. |
| initTarget | To initialize target, hierarchical correlation algorithm. |
| initTarget.details | To initialize target, hierarchical correlation algorithm. |
| matrixDistance | Matrix distance by distance type |
| maxDistance | Maximal distance |
| maxDistance.details | Maximal distance |
| mdAgglomerative | Matrix distance by distance and approach type. |
| mdAgglomerative.details | Matrix distance by distance and approach type. |
| mdDivisive | Matrix distance by distance and approach type. |
| mdDivisive.details | Matrix distance by distance and approach type. |
| mdistance | To calculate the Manhattan distance. |
| mdistance.details | To explain how to calculate the Manhattan distance. |
| mdistanceW | To calculate the Manhattan distance applying weights. |
| mdistanceW.details | To calculate the Manhattan distance applying weights. |
| minDistance | Minimal distance |
| minDistance.details | Minimal distance |
| newCluster | To create a new cluster. |
| newCluster.details | To explain how to create a new cluster. |
| normalizeWeight | To normalize weight values. |
| normalizeWeight.details | To normalize weight values. |
| octileDistance | To calculate the Octile distance. |
| octileDistance.details | To explain how to calculate the Octile distance. |
| octileDistanceW | To calculate the Octile distance applying weights. |
| octileDistanceW.details | To calculate the Octile distance applying weights. |
| toList | To transform data into list |
| toList.details | To explain how to transform data into list |
| toListDivisive | To transform data into list |
| toListDivisive.details | To explain how to transform data into list |
| usefulClusters | To delete clusters grouped. |