{ "_id": "6a27cf7624555f66ed544b6f", "Package": "LearnClust", "Type": "Package", "Date": "2020-11-24", "Title": "Learning Hierarchical Clustering Algorithms", "Version": "1.1", "Authors@R": "c(\nperson(\"Roberto\",\"Alcantara\", role = c(\"aut\",\"cre\"),\nemail = \"roberto.alcantara@edu.uah.es\"),\nperson(\"Juan Jose Cuadrado\", role = c(\"aut\"),\nemail = \"jjcg@uah.es\"),\nperson(\"Universidad de Alcala de Henares\", role = c(\"aut\"))\n)", "Author": "Roberto Alcantara [aut, cre], Juan Jose Cuadrado [aut],\nUniversidad de Alcala de Henares [aut]", "Maintainer": "Roberto Alcantara ", "Description": "Classical hierarchical clustering algorithms,\nagglomerative and divisive clustering. Algorithms are\nimplemented as a theoretical way, step by step. It includes\nsome detailed functions that explain each step. Every function\nallows options to get different results using different\ntechniques. 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"topics": [ "agglomerativeHC" ] }, { "page": "agglomerativeHC.details", "title": "To explain agglomerative hierarchical clusterization algorithm by distance and approach.", "topics": [ "agglomerativeHC.details" ] }, { "page": "canberradistance", "title": "To calculate the Canberra distance.", "topics": [ "canberradistance" ] }, { "page": "canberradistance.details", "title": "To show the formula and to return the Canberra distance.", "topics": [ "canberradistance.details" ] }, { "page": "canberradistanceW", "title": "To calculate the Canberra distance applying weights.", "topics": [ "canberradistanceW" ] }, { "page": "canberradistanceW.details", "title": "To calculate the Canberra distance applying weights .", "topics": [ "canberradistanceW.details" ] }, { "page": "chebyshevDistance", "title": "To calculate the Chebyshev distance.", "topics": [ "chebyshevDistance" ] }, { "page": "chebyshevDistance.details", "title": "To show the formula of the Chebyshev distance.", "topics": [ "chebyshevDistance.details" ] }, { "page": "chebyshevDistanceW", "title": "To calculate the Chebyshev distance applying weights.", "topics": [ "chebyshevDistanceW" ] }, { "page": "chebyshevDistanceW.details", "title": "To calculate the Chebyshev distance applying weights.", "topics": [ "chebyshevDistanceW.details" ] }, { "page": "clusterDistance", "title": "To calculate the distance between clusters.", "topics": [ "clusterDistance" ] }, { "page": "clusterDistance.details", "title": "To explain how to calculate the distance between clusters.", "topics": [ "clusterDistance.details" ] }, { "page": "clusterDistanceByApproach", "title": "To calculate the distance by approach option.", "topics": [ "clusterDistanceByApproach" ] }, { "page": "clusterDistanceByApproach.details", "title": "To explain how to calculate the distance by approach option.", "topics": [ "clusterDistanceByApproach.details" ] }, { "page": "complementaryClusters", "title": "To check if two clusters are complementary", "topics": [ "complementaryClusters" ] }, { "page": "complementaryClusters.details", "title": "To explain how and why two clusters are complementary.", "topics": [ "complementaryClusters.details" ] }, { "page": "correlationHC", "title": "To execute hierarchical correlation algorithm.", "topics": [ "correlationHC" ] }, { "page": "correlationHC.details", "title": "To explain how hierarchical correlation algorithm works.", "topics": [ "correlationHC.details" ] }, { "page": "distances", "title": "To calculate distances applying weights.", "topics": [ "distances" ] }, { "page": "distances.details", "title": "To calculate distances applying weights.", "topics": [ "distances.details" ] }, { "page": "divisiveHC", "title": "To execute divisive hierarchical clusterization algorithm by distance and approach.", "topics": [ "divisiveHC" ] }, { "page": "divisiveHC.details", "title": "To explain the divisive hierarchical clusterization algorithm by distance and approach.", "topics": [ "divisiveHC.details" ] }, { "page": "edistance", "title": "To calculate the Euclidean distance.", "topics": [ "edistance" ] }, { "page": "edistance.details", "title": "To show the Euclidean distance formula.", "topics": [ "edistance.details" ] }, { "page": "edistanceW", "title": "To calculate the Euclidean distance applying weights.", "topics": [ "edistanceW" ] }, { "page": "edistanceW.details", "title": "To calculate the Euclidean distance applying weights.", "topics": [ "edistanceW.details" ] }, { "page": "getCluster", "title": "To get the clusters with minimal distance.", "topics": [ "getCluster" ] }, { "page": "getCluster.details", "title": "To explain how to get the clusters with minimal distance.", "topics": [ "getCluster.details" ] }, { "page": "getClusterDivisive", "title": "To get the clusters with maximal distance.", "topics": [ "getClusterDivisive" ] }, { "page": "getClusterDivisive.details", "title": "To explain how to get the clusters with maximal distance.", "topics": [ "getClusterDivisive.details" ] }, { "page": "initClusters", "title": "To initialize clusters for the divisive algorithm.", "topics": [ "initClusters" ] }, { "page": "initClusters.details", "title": "To explain how to initialize clusters for the divisive algorithm.", "topics": [ "initClusters.details" ] }, { "page": "initData", "title": "To initialize data, hierarchical correlation algorithm.", "topics": [ "initData" ] }, { "page": "initData.details", "title": "To initialize data, hierarchical correlation algorithm.", "topics": [ "initData.details" ] }, { "page": "initImages", "title": "To display an image.", "topics": [ "initImages" ] }, { "page": "initTarget", "title": "To initialize target, hierarchical correlation algorithm.", "topics": [ "initTarget" ] }, { "page": "initTarget.details", "title": "To initialize target, hierarchical correlation algorithm.", "topics": [ "initTarget.details" ] }, { "page": "matrixDistance", "title": "Matrix distance by distance type", "topics": [ "matrixDistance" ] }, { "page": "maxDistance", "title": "Maximal distance", "topics": [ "maxDistance" ] }, { "page": "maxDistance.details", "title": "Maximal distance", "topics": [ "maxDistance.details" ] }, { "page": "mdAgglomerative", "title": "Matrix distance by distance and approach type.", "topics": [ "mdAgglomerative" ] }, { "page": "mdAgglomerative.details", "title": "Matrix distance by distance and approach type.", "topics": [ "mdAgglomerative.details" ] }, { "page": "mdDivisive", "title": "Matrix distance by distance and approach type.", "topics": [ "mdDivisive" ] }, { "page": "mdDivisive.details", "title": "Matrix distance by distance and approach type.", "topics": [ "mdDivisive.details" ] }, { "page": "mdistance", "title": "To calculate the Manhattan distance.", "topics": [ "mdistance" ] }, { "page": "mdistance.details", "title": "To explain how to calculate the Manhattan distance.", "topics": [ "mdistance.details" ] }, { "page": "mdistanceW", "title": "To calculate the Manhattan distance applying weights.", "topics": [ "mdistanceW" ] }, { "page": "mdistanceW.details", "title": "To calculate the Manhattan distance applying weights.", "topics": [ "mdistanceW.details" ] }, { "page": "minDistance", "title": "Minimal distance", "topics": [ "minDistance" ] }, { "page": "minDistance.details", "title": "Minimal distance", "topics": [ "minDistance.details" ] }, { "page": "newCluster", "title": "To create a new cluster.", "topics": [ "newCluster" ] }, { "page": "newCluster.details", "title": "To explain how to create a new cluster.", "topics": [ "newCluster.details" ] }, { "page": "normalizeWeight", "title": "To normalize weight values.", "topics": [ "normalizeWeight" ] }, { "page": "normalizeWeight.details", "title": "To normalize weight values.", "topics": [ "normalizeWeight.details" ] }, { "page": "octileDistance", "title": "To calculate the Octile distance.", "topics": [ "octileDistance" ] }, { "page": "octileDistance.details", "title": "To explain how to calculate the Octile distance.", "topics": [ "octileDistance.details" ] }, { "page": "octileDistanceW", "title": "To calculate the Octile distance applying weights.", "topics": [ "octileDistanceW" ] }, { "page": "octileDistanceW.details", "title": "To calculate the Octile distance applying weights.", "topics": [ "octileDistanceW.details" ] }, { "page": "toList", "title": "To transform data into list", "topics": [ "toList" ] }, { "page": "toList.details", "title": "To explain how to transform data into list", "topics": [ "toList.details" ] }, { "page": "toListDivisive", "title": "To transform data into list", "topics": [ "toListDivisive" ] }, { "page": "toListDivisive.details", "title": "To explain how to transform data into list", "topics": [ "toListDivisive.details" ] }, { "page": "usefulClusters", "title": "To delete clusters grouped.", "topics": [ "usefulClusters" ] } ], "_rundeps": [ "curl", "magick", "magrittr", "Rcpp" ], "_vignettes": [ { "source": "LearnClust.Rmd", "filename": 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