-stage clustering (Self-Organization Maps and K-means), this research identified different types of departments-including physicians …

The data mining technique of time series clustering is well established in many fields. However, as an unsupervised … this paper is to verify usefulness of the time series clustering method for macroeconomics research, and to develop the … (compression-based dissimilarity measure, or CDM) which is particularly suitable for clustering macroeconomic variables. We check …

in condition monitoring. The identification of operation profiles during production is therefore important. Clustering …-and-effect relationship between the operation regimes and the wear level of components. In this study unsupervised clustering technique was …

the same regression curve. We develop a bandwidth-free clustering method to estimate the unknown group structure from the …

-Rubin tests, optionally with (multi-way) clustering. We review the main ideas of the wild cluster bootstrap, offer tips for use …

structure makes such demand outliers hard to detect. We propose a two-step approach combining clustering with functional outlier …

The role of ethnic clustering in ethnic identity formation has remained unexplored, mainly due to missing detailed data … clustering strengthens immigrants' retention of an affiliation with their origin (minority identity), it weakens identification …

multiple operations, we employ a clustering approach on 69 firm characteristics and allocate companies to novel economic … to quantify feature importance for clustering methods, finding that size drives differences across classical industries … while book-to-market and financial liquidity variables matter for clustering-based sectors. …