HierarchicalClustering (FSharp.Stats)

HierarchicalClustering Module

Namespace: FSharp.Stats.ML.Unsupervised
Assembly: FSharp.Stats.dll

Types and nested modules

Type/Module	Description
Linker	The linkage criterion determines the distance between sets of observations as a function of the pairwise distances between observations
Cluster<'T>	Binary distance tree
ClusterIndex
Distance<'a>	Euclidean distance of two coordinate arrays
DistanceCaching<'T>	Class for chaching already calculated distances to speed up cluster build

Functions and values

Function or value	Description
`aggregateClusterBy predicate cluster` Full Usage: `aggregateClusterBy predicate cluster` Parameters: predicate : `float -> int -> bool` - cluster : `Cluster<'T>` - Returns: `Cluster<'T list>`	Aggregates the subbranches of a node to leafs, if the predicate function taking the distance and the number of subLeafs returns true predicate : `float -> int -> bool` cluster : `Cluster<'T>` Returns: `Cluster<'T list>` Example
`aggregateClusterByDistance distanceCutoff cluster` Full Usage: `aggregateClusterByDistance distanceCutoff cluster` Parameters: distanceCutoff : `float` - cluster : `Cluster<'T>` - Returns: `Cluster<'T list>`	Aggregates the subbranches of a node to leafs, if the distance between them is smaller than the given distanceCutoff distanceCutoff : `float` cluster : `Cluster<'T>` Returns: `Cluster<'T list>` Example
`createCluster id dist left right` Full Usage: `createCluster id dist left right` Parameters: id : `int` dist : `float` left : `Cluster<'T>` right : `Cluster<'T>` Returns: `Cluster<'T>`	Create a cluster Node containing the two given subbranches id : `int` dist : `float` left : `Cluster<'T>` right : `Cluster<'T>` Returns: `Cluster<'T>`
`createClusterValue id value` Full Usage: `createClusterValue id value` Parameters: id : `int` - value : `'T` - Returns: `Cluster<'T>`	Create a cluster Leaf id : `int` value : `'T` Returns: `Cluster<'T>` Example
`cutHClust desiredNumber clusterTree` Full Usage: `cutHClust desiredNumber clusterTree` Parameters: desiredNumber : `int` - clusterTree : `Cluster<float array>` - Returns: `Cluster<float array> list list`	cuts tree in chosen amount of clusters desiredNumber : `int` clusterTree : `Cluster<float array>` Returns: `Cluster<float array> list list` Example
`euclidean a1 a2` Full Usage: `euclidean a1 a2` Parameters: a1 : `^a array` a2 : `^a array` Returns: `float` Modifiers: inline	a1 : `^a array` a2 : `^a array` Returns: `float`
`flattenHClust clusterTree` Full Usage: `flattenHClust clusterTree` Parameters: clusterTree : `Cluster<float array>` Returns: `Cluster<float array> list`	clusterTree : `Cluster<float array>` Returns: `Cluster<float array> list`
`fromFileWithSep separator filePath` Full Usage: `fromFileWithSep separator filePath` Parameters: separator : `char` filePath : `string` Returns: `seq<string[]>`	separator : `char` filePath : `string` Returns: `seq<string[]>`
`generate distance linker data` Full Usage: `generate distance linker data` Parameters: distance : `Distance<float[]>` linker : `LancWilliamsLinker` data : `float[] array` Returns: `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`	Builds a hierarchy of clusters of data containing cluster labels distance : `Distance<float[]>` linker : `LancWilliamsLinker` data : `float[] array` Returns: `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`
`get clusterTree` Full Usage: `get clusterTree` Parameters: clusterTree : `Cluster<float array>` - Returns: `seq<float * int * int>`	Converts clusters into string seq clusterTree : `Cluster<float array>` Returns: `seq<float * int * int>` Example
`getClusterId c` Full Usage: `getClusterId c` Parameters: c : `Cluster<'T>` - Returns: `int`	Returns cluster Id c : `Cluster<'T>` Returns: `int` Example
`getClusterMemberCount c` Full Usage: `getClusterMemberCount c` Parameters: c : `Cluster<'T>` - Returns: `int`	Returns cluster member count c : `Cluster<'T>` Returns: `int` Example
`getClusterMemberLabels cluster` Full Usage: `getClusterMemberLabels cluster` Parameters: cluster : `Cluster<'a>` Returns: `int list list`	cluster : `Cluster<'a>` Returns: `int list list`
`getDistance cluster` Full Usage: `getDistance cluster` Parameters: cluster : `Cluster<'a>` Returns: `float`	cluster : `Cluster<'a>` Returns: `float`
`getDistancesAndLabels cluster` Full Usage: `getDistancesAndLabels cluster` Parameters: cluster : `Cluster<'T>` - Returns: `(int * float) list`	Returns a list of the distances between the subclusters cluster : `Cluster<'T>` Returns: `(int * float) list` Example
`getDistancesOfCluster cluster` Full Usage: `getDistancesOfCluster cluster` Parameters: cluster : `Cluster<'T>` - Returns: `float list`	Returns a list of the distances between the subclusters cluster : `Cluster<'T>` Returns: `float list` Example
`getLeafNamesOfCluster cluster` Full Usage: `getLeafNamesOfCluster cluster` Parameters: cluster : `Cluster<'T>` - Returns: `int list`	Returns a list of the leaf names cluster : `Cluster<'T>` Returns: `int list` Example
`getLeafsOfCluster cluster` Full Usage: `getLeafsOfCluster cluster` Parameters: cluster : `Cluster<'T>` - Returns: `'T list`	Returns a list of the leaf names cluster : `Cluster<'T>` Returns: `'T list` Example
`getLeftChild cluster` Full Usage: `getLeftChild cluster` Parameters: cluster : `Cluster<'a>` Returns: `Cluster<'a>`	cluster : `Cluster<'a>` Returns: `Cluster<'a>`
`getRightChild cluster` Full Usage: `getRightChild cluster` Parameters: cluster : `Cluster<'a>` Returns: `Cluster<'a>`	cluster : `Cluster<'a>` Returns: `Cluster<'a>`
`getWithClusterName clusterTree` Full Usage: `getWithClusterName clusterTree` Parameters: clusterTree : `Cluster<float array>` Returns: `seq<int * float * int * int>`	clusterTree : `Cluster<float array>` Returns: `seq<int * float * int * int>`
`initPairsNR cachedDist arr` Full Usage: `initPairsNR cachedDist arr` Parameters: cachedDist : `DistanceCaching<float[]>` arr : `float[] array` Returns: `Dictionary<Cluster<float[]>, FastPriorityQueue<ClusterIndex>>`	cachedDist : `DistanceCaching<float[]>` arr : `float[] array` Returns: `Dictionary<Cluster<float[]>, FastPriorityQueue<ClusterIndex>>`
`mapClusterLeaftags mapF cluster` Full Usage: `mapClusterLeaftags mapF cluster` Parameters: mapF : `'T -> 'U` - cluster : `Cluster<'T>` - Returns: `Cluster<'U>`	Maps the tags of the leafs of the cluster by applying a given mapping function mapF : `'T -> 'U` cluster : `Cluster<'T>` Returns: `Cluster<'U>` Example
`minDequeue source` Full Usage: `minDequeue source` Parameters: source : `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>` Returns: `KeyValuePair<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`	source : `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>` Returns: `KeyValuePair<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`
`printHClust clusterTree` Full Usage: `printHClust clusterTree` Parameters: clusterTree : `Cluster<float array>` - Returns: `seq<string>`	Converts clusters into string seq clusterTree : `Cluster<float array>` Returns: `seq<string>` Example
`tryGetLeafValue c` Full Usage: `tryGetLeafValue c` Parameters: c : `Cluster<'T>` - Returns: `'T option`	Returns cleaf value c : `Cluster<'T>` Returns: `'T option` Example
`usedDistancesAndLabels cluster` Full Usage: `usedDistancesAndLabels cluster` Parameters: cluster : `Cluster<'a>` Returns: `(float * int list) list`	cluster : `Cluster<'a>` Returns: `(float * int list) list`
`whileLoop cachedDist source countIndex` Full Usage: `whileLoop cachedDist source countIndex` Parameters: cachedDist : `DistanceCaching<float[]>` source : `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>` countIndex : `int` Returns: `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`	cachedDist : `DistanceCaching<float[]>` source : `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>` countIndex : `int` Returns: `Dictionary<Cluster<float array>, FastPriorityQueue<ClusterIndex>>`

HierarchicalClustering Module

Types and nested modules

Functions and values

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