Sparse and smooth functional data clustering

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 Sparse Binary Data

Clustering Large and Sparse Co-occurrence Data

A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory — in this framework, an optimal clustering is one which minimizes the loss in mutual information. Recently a divisive clustering algorithm was proposed that monotonically reduces this loss function. In this paper we show that sparse high-dimensional data presents special challenges which ...

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...