نتایج جستجو برای: maximum likelihood classifier

تعداد نتایج: 398600  

Journal: :The Annals of Statistics 1998

Journal: :The International Journal of Biostatistics 2006

Journal: :The Annals of Statistics 2010

Journal: :American Journal of Mathematics 2006

2010
Xiaoyang Fu Shuqing Zhang Zhenping Pang

A resource limited immune approach (RLIA) was developed to evolve architecture and initial connection weights of multilayer neural networks. Then, with Back-Propagation (BP) algorithm, the appropriate connection weights can be found. The RLIA-BP classifier, which is derived from hybrid algorithm mentioned above, is demonstrated on SPOT multi-spectral image data, vowel data and Iris data effecti...

Journal: :IEEE Trans. Geoscience and Remote Sensing 1999
Byeungwoo Jeon David A. Landgrebe

This paper propose two decision fusion-based multitemporal classifiers, namely, the jointly likelihood and the weighted majority fusion classifiers, that are derived using two different definitions of the minimum expected cost. Without any overhead incurred by multitemporal processing, a user-selected conventional pixelwise classifier makes local class decisions separately using each temporal d...

2011
A M. MUSLIM

Accurate, up-to-date and accessible information on the state of coral reef ecosystem is necessary for informed and effective management of these important marine resources. However, environments containing these habitats are challenging to map due to their remoteness, extent and costs of monitoring. In this research, the capabilities of satellite remote sensing techniques combined with in situ ...

1998
Vanessa Didelez Iris Pigeot

In this paper we discuss maximum likelihood estimation when some observations are missing in mixed graphical interaction models assuming a conditional Gaussian distribution as introduced by Lauritzen & Wermuth (1989). For the saturated case ML estimation with missing values via the EM algorithm has been proposed by Little & Schluchter (1985). We expand their results to the special restrictions ...

2011
Peter Beerli Fredrik Ronquist

Assume that we have some data D and a model M of the process that generated the data. The model has some parameters θ, the specific value of which we do not know but wish to estimate. If the model is properly constructed, we will be able to calculate the probability of it generating the observed data given a specific set of parameter values, P (D|θ,M). Often, the conditioning on the model is su...

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