This site uses cookies.
Some of these cookies are essential to the operation of the site,
while others help to improve your experience by providing insights into how the site is being used.
For more information, please see the ProZ.com privacy policy.
Traductor o intérprete autónomo, Identidad verificada
Data security
This person has a SecurePRO™ card. Because this person is not a ProZ.com Plus subscriber, to view his or her SecurePRO™ card you must be a ProZ.com Business member or Plus subscriber.
Afiliaciones
This person is not affiliated with any business or Blue Board record at ProZ.com.
Servicios
Translation
Especialización
Se especializa en
Informática (general)
Informática: Sistemas, redes
TI (Tecnología de la información)
Electrónica / Ing. elect.
Medicina: Instrumentos
Informática: Programas
Patentes
Física
Ciencias (general)
Ingeniería (general)
También trabaja en
Derecho: contrato(s)
Construcción / Ingeniería civil
Matemáticas y estadística
Telecomunicaciones
Encuestas
Derecho: patentes, marcas registradas, derechos de autor
Contabilidad
Medios / Multimedia
Juegos / Videojuegos / Apuestas / Casino
Automóviles / Camiones
More
Less
Tarifas
portugués al japonés - Tarifas: 0.12 - 0.17 USD por palabra español al japonés - Tarifas: 0.12 - 0.17 USD por palabra japonés al inglés - Tarifas: 0.10 - 0.15 USD por caracter
Puntos de nivel PRO 194, Preguntas respondidas: 92, Preguntas formuladas: 2
Historial de proyectos
0 proyectos mencionados
Muestrario
Muestras de traducción: 1
inglés al japonés: Bayesian network classifiers ベイジアンネットワーク識別器
Texto de origen - inglés Bayesian network classifiers
N. Friedman, D. Geiger,
and M. Goldszmidt
Machine Learning 29:131--163, 1997.
Abstract
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with state-of-the-art classifiers such as C4.5.
This fact raises the question of whether a classifier with less restrictive assumptions can perform even better.
In this paper we evaluate approaches for inducing classifiers from data, based on the theory of learning Bayesian networks.
Bayesian networks are factored representations of probability distributions that generalize the naive Bayesian classifier and explicitly represent statements about independence.
Among these approaches we single out a method we call Tree Augmented Naive Bayes (TAN), which outperforms naive Bayes, yet at the same time maintains the computational simplicity (no search involved) and robustness that are characteristic of naive Bayes.
We experimentally tested these approaches, using benchmark problems from the University of California at Irvine repository, and compared them to C4.5, naive Bayes, and wrapper-based feature selection methods.
Traducción - japonés ベイジアンネットワーク識別器
N. フリードマン, D. ゲイジャー,
M. ゴールドスミス
機械学習 29:131--163, 1997.
Received Doctor of Science degree in physics from Tohoku University in 1987.
Worked for the Computer College of Iwasaki Gakuen from 1985 to 1991.
Worked for EXA Corp., IT company, from 1991 to 2005.
Published several scientific papers in English.
Translated software manuals, scientific papers, patent documents, etc.
Specialize in
Computers, IT, Engineering, Science, Mathematics & Statistics, Physics, etc.
Este miembro obtuvo puntos KudoZ al ayudar a otros traductores a traducir términos de nivel PRO. Haga clic en total(es) de puntos para ver los términos traducidos.
Total de ptos. obtenidos: 206 Puntos de nivel PRO: 194