نتایج جستجو برای: multinomial logistic regression

تعداد نتایج: 331786  

1995
Eric Sven Ristad

Consider the problem of multinomial estimation. You are given an alphabet of distinct symbols and are told the frequency with which each symbol occurred in the past. On the basis of this information alone, you must now estimate the symbol probabilities. In this report, we present a new solution to this fundamental problem in statistics and demonstrate that our solution outperforms standard appr...

2013
Tomas Brychcin Ivan Habernal

Current approaches to document-level sentiment analysis rely on local information, e.g., the words within the given document. We try to achieve better performance by incorporating global context of the sentiment target (e.g., a movie or a product). We assume that sentiment labels of reviews about the same target are often consistent in some way. We model this consistency by Dirichlet distributi...

2015
Wanqiu Kou Fang Li Timothy Baldwin

The native representation of LDA-style topics is a multinomial distributions over words, but automatic labelling of such topics has been shown to help readers interpret the topics better. We propose a novel framework for topic labelling using word vectors and letter trigram vectors. We generate labels automatically and propose automatic and human evaluations of our method. First, we use a chunk...

Journal: :JLCL 2014
Katerina Veselovská Jan Hajic Jana Sindlerová

The aim of this paper is to introduce the Czech subjectivity lexicon, a new lexical resource for sentiment analysis in Czech. We describe particular stages of the manual refinement of the lexicon and demonstrate its use in the state-of-the art polarity classifiers, namely the Maximum Entropy classifier. We test the success rate of the system enriched with the dictionary on different data sets, ...

2015
Qing Dou Ashish Vaswani Kevin Knight Chris Dyer

We introduce into Bayesian decipherment a base distribution derived from similarities of word embeddings. We use Dirichlet multinomial regression (Mimno and McCallum, 2012) to learn a mapping between ciphertext and plaintext word embeddings from non-parallel data. Experimental results show that the base distribution is highly beneficial to decipherment, improving state-of-the-art decipherment a...

2013
Karim Anaya-Izquierdo Frank Critchley Paul Marriott Paul Vos

This paper applies the tools of computation information geometry [3] – in particular, high dimensional extended multinomial families as proxies for the ‘space of all distributions’ – in the inferentially demanding area of statistical mixture modelling. A range of resultant benefits are noted.

2017
KORAY KAYABOL

Abstract: We propose the sparse multinomial logistic regression (SMLR) model for spectral-spatial classification of hyperspectral images. In the proposed method, the parameters of SMLR are iteratively estimated from logposterior by using Laplace approximation. The proposed update rule provides a faster convergence compared to the state-of the-art methods used for SMLR parameter estimation. The ...

2011
Mohammad Anisi Morteza Analoui

Nowadays one of the most important challenges for integrated systems such as social networks is the evaluation of trust for agents which are interacting with each other in the environment. It plays an important role that the trust has been evaluated from the agent’s experiences. In this paper, we propose a new mathematical approach based on the entropy of Dirichlet distribution, to model the ag...

2009
Zhiheng Huang Marcus Thint Asli Çelikyilmaz

In this paper, we investigate how an accurate question classifier contributes to a question answering system. We first present a Maximum Entropy (ME) based question classifier which makes use of head word features and their WordNet hypernyms. We show that our question classifier can achieve the state of the art performance in the standard UIUC question dataset. We then investigate quantitativel...

1997
Michel Bierlaire

Discrete choice models have played an important role in transportation modeling for the last 25 years. They are namely used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justiications. Moreover, several packages and tools are available to help practionners using these models for real applications, making discrete choice models ...

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