Aggregation function#

Descriptions of the basic functions are given below.

Function descriptions:

periodAggregation.aggregatePeriods(candidates, n_clusters=8, n_iter=100, clusterMethod='k_means', solver='highs', representationMethod=None, representationDict=None, distributionPeriodWise=True, timeStepsPerPeriod=None)[source]#

Clusters the data based on one of the cluster methods: ‘averaging’, ‘k_means’, ‘exact k_medoid’ or ‘hierarchical’

Parameters:

  • candidates (np.ndarray) – Dissimilarity matrix where each row represents a candidate. required

  • n_clusters (integer) – Number of aggregated cluster. optional (default: 8)

  • n_iter (integer) – Only required for the number of starts of the k-mean algorithm. optional (default: 10)

  • clusterMethod (string) – Chosen clustering algorithm. Possible values are ‘averaging’,’k_means’,’exact k_medoid’ or ‘hierarchical’. optional (default: ‘k_means’)