نتایج جستجو برای: a cluster sampling

تعداد نتایج: 13494356  

Journal: :Comput. Geom. 2005
Yogish Sabharwal Sandeep Sen

Matousek [Discrete Comput. Geom. 24 (1) (2000) 61–84] designed an O(nlogn) deterministic algorithm for the approximate 2-means clustering problem for points in fixed dimensional Euclidean space which had left open the possibility of a linear time algorithm. In this paper, we present a simple randomized algorithm to determine an approximate 2-means clustering of a given set of points in fixed di...

2004
Bruno Cortes José Nuno Oliveira

This paper presents a strategy for applying sampling techniques to relational databases, in the context of data quality auditing or decision support processes. Fuzzy cluster sampling is used to survey sets of records for correctness of business rules. Relational algebra estimators are presented as a data quality-auditing tool.

1998
Joel Hasbrouck

This paper proposes a dynamic model of bid and ask quotes that incorporates a stochastic cost of market-making, discreteness (restriction of quotes to a fixed grid) and clustering (the tendency of quotes to lie on " natural " multiples of the tick size). The Gibbs sampler provides a convenient vehicle for estimation. The model is estimated for daily and intradaily US Dollar/Deutschemark Reuters...

Journal: :Journal of the National Science Foundation of Sri Lanka 2019

Journal: :International Journal of Advanced Computer Science and Applications 2017

Journal: :Bioinformatics 2002
Gert Thijs Yves Moreau Frank De Smet Janick Mathys Magali Lescot Stephane Rombauts Pierre Rouzé Bart De Moor Kathleen Marchal

INCLUSive allows automatic multistep analysis of microarray data (clustering and motif finding). The clustering algorithm (adaptive quality-based clustering) groups together genes with highly similar expression profiles. The upstream sequences of the genes belonging to a cluster are automatically retrieved from GenBank and can be fed directly into Motif Sampler, a Gibbs sampling algorithm that ...

2006
Shubhankar Ray Bani Mallick B. Mallick

We propose a nonparametric Bayes wavelet model for clustering of functional data. The wavelet-based methodology is aimed at the resolution of generic global and local features during clustering and is suitable for clustering high dimensional data. Based on the Dirichlet process, the nonparametric Bayes model extends the scope of traditional Bayes wavelet methods to functional clustering and all...

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