Functional Clustering Based on Weighted Partitioning around Medoid Algorithm with Estimation of Number of Clusters
Jianan Zhang · 2021
More and more data are recorded continuously in an interval or discretely only at finite time points nowadays due to the frequency of data collection. These data are functional data which belong to big data. This paper introduces functional clustering in functional data analysis. We propose a weighted partitioning around medoid algorithm with estimation of number of clusters for functional clustering, and use an example to prove its effectiveness.