Sparse clustering of functional data

Clustering of Sparse Binary Data

the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance

با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...

Clustering of Conceptual Graphs with Sparse Data

This paper gives a theoretical framework for clustering a set of conceptual graphs characterized by sparse descriptions. The formed clusters are named in an intelligible manner through the concept of stereotype, based on the notion of default generalization. The cognitive model we propose relies on sets of stereotypes and makes it possible to save data in a structured memory.

Clustering for functional data

This work proposes an unsupervised classification algorithm for curves. It extends the density based multivariate cluster approach to the functional framework. In particular, the modes of the small-ball probability are used as starting points to build the clusters. A simulation study is proposed.

Clustering multivariate functional data

Model-based clustering is considered for Gaussian multivariate functional data as an extension of the univariate functional setting. Principal components analysis is introduced and used to define an approximation of the notion of density for multivariate functional data. An EM like algorithm is proposed to estimate the parameters of the reduced model. Application on climatology data illustrates...