Model-based clustering of meta-analytic functional imaging data
نویسندگان
چکیده
منابع مشابه
Model-based clustering of meta-analytic functional imaging data.
We present a method for the analysis of meta-analytic functional imaging data. It is based on Activation Likelihood Estimation (ALE) and subsequent model-based clustering using Gaussian mixture models, expectation-maximization (EM) for model fitting, and the Bayesian Information Criterion (BIC) for model selection. Our method facilitates the clustering of activation maxima from previously perfo...
متن کاملModel - based clustering of functional data ∗
Model-based clustering for functional data is considered. An alternative to model-based clustering using the functional principal components is proposed by approximating the density of functional random variables. The EM algorithm is used for parameter estimation and the maximum a posteriori rule provides the clusters. Simulation study and real data application illustrate the interest of the pr...
متن کاملModel-based clustering for multivariate functional data
This paper proposes the first model-based clustering algorithm for multivariate functional data. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, based on the assumption of normality of the principal components, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into accoun...
متن کاملModel-Based Clustering and Classification of Functional Data
The problem of complex data analysis is a central topic of modern statistical science and learning systems and is becoming of broader interest with the increasing prevalence of highdimensional data. The challenge is to develop statistical models and autonomous algorithms that are able to acquire knowledge from raw data for exploratory analysis, which can be achieved through clustering technique...
متن کاملEntropy-based Consensus for Distributed Data Clustering
The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Human Brain Mapping
سال: 2008
ISSN: 1065-9471,1097-0193
DOI: 10.1002/hbm.20380