Seq the algorithm which will be launched with various parameters
the dataset of clusterizable
Necessary security for specific algorithm which require to have same data order
the current vectorization employed
Indices of launched algorithm, ie (previousClusteringNumber until previousClusteringNumber + algorithms.size)
ParSeq of Collection of ClusterID, each ParSeq elem correspond to the given algorithms order
get all models resulting from given clustering algorithm
get one model from those resulting from given clustering algorithm
get all models resulting from given clustering algorithm for a particular vectorization
Model Mapping required to access to specific model in ModelsKeeper HMAP
The Dataset vectorization is the original one
The Dataset vectorization is the original one
the linked dataset between clusterizable and their associate clusteringIDs sorted by clusterizable ID
This classe intend to run many algorithms parallely on a local system for medium size datasets, it works for one version of an algorithm with various parameters
the raw object from which vectorizations came from
the nature of the working vector
a clusterizable descendant, EasyClusterizable is the basic advise instance
the nature of the collection containing Cz[O, V]
the current vectorization which gives the current Vector nature
the clustering model type corresponding to the nature of the given algorithm type
the clustering algorith type