搜索结果: 1-15 共查到“理论统计学 Bayes”相关记录26条 . 查询时间(0.254 秒)
Testing the statistical significance of an ultra-high-dimensional naïve Bayes classfier
Binary Predictor Hypothesis Testing Na?ve Bayes Supervised Learning
2016/1/25
The na?ve Bayes approach is one of the most popular methods used for classi?cation. Nevertheless, how to test its statistical signi?cance under an ultra-high-dimensional (UHD) setup is not well unders...
Testing the statistical significance of an ultra-high-dimensional naïve Bayes classfier
Binary Predictor Hypothesis Testing Na?ve Bayes Supervised Learning
2016/1/20
The na?ve Bayes approach is one of the most popular methods used for classi?cation. Nevertheless, how to test its statistical signi?cance under an ultra-high-dimensional(UHD) setup is not well underst...
Adaptive Bayes test for monotonicity
Bayesian Nonparametric Nonparametric regression Nonparamet-ric hypothesis testing Asymptotic properties
2013/4/28
We study the asymptotic behaviour of a Bayesian nonparametric test of qualitative hypotheses. More precisely, we focus on the problem of testing monotonicity of a regression function. Even if some res...
Refinement revisited with connections to Bayes error, conditional entropy and calibrated classifiers
Refinement Score Probability Elicitation Calibrated Classifier Bayes Error Bound Conditional Entropy Proper Loss
2013/4/27
The concept of refinement from probability elicitation is considered for proper scoring rules. Taking directions from the axioms of probability, refinement is further clarified using a Hilbert space i...
Bounds on the Maximum Bayes Error Given Moments
the Maximum Bayes Error class-conditional Curto Fialkow’s solutions
2011/6/17
We show how to compute lower bounds for the maximum possible Bayes error if the class-conditional distributions
must satisfy moment constraints. Our approach makes use of Curto and Fialkow’s solution...
Variational Bayes approach for model aggregation in unsupervised classification with Markovian dependency
Model averaging Variational Bayes inference Markov Chain Unsu-pervised classification
2011/6/16
We consider a binary unsupervised classi cation problem where each observation
is associated with an unobserved label that we want to retrieve. More precisely, we
assume that there are two groups of...
基于Bayes概率边界域的粗集分类方法及其在高频数据中的应用
可变精度粗糙集 Bayes边界域 高频数据
2013/8/23
作为一种近似处理的工具，粗集主要用于不确定情况下的决策分析，并且不需要任何事先的数据假定。但当前的主流粗集分类方法仍然需要先经过离散化的步骤，这就损失了数值型变量提供的高质量信息。本文对隶属函数重新加以概率定义，并提出了一种基于Bayes概率边界域的粗集分类技术，比较好地解决了当前粗集方法所面临的数值型属性分类的不适应、分类规则不完备等一系列问题。
The Bayes oracle and asymptotic optimality of multiple testing procedures under sparsity
Multiple testing FDR Bayes oracle asymptotic optimality
2010/3/10
We investigate the asymptotic optimality of a large class of multiple testing rules using the
framework of Bayesian Decision Theory. We consider a parametric setup, in which observations
come from a...
Bayes,Jeffreys,Prior Distributions and the Philosophy of Statistics
Bayes Jeffreys Prior Distributions Philosophy of Statistics
2010/3/9
I actually own a copy of Harold Jeffreys’s The-
ory of Probability but have only read small bits of
it, most recently over a decade ago to confirm that,
indeed, Jeffreys was not too proud to use a ...
Bayes One-Sample and One-Way Random Effects Analyses for 3-D Orientations with Application to Materials Science
ayes credible intervals Electron backscatter diffraction Gibbs Metropolis-Hastings one-way random effects model
2009/9/24
We consider Bayes inference for a class of distributions on orientations in 3 dimensions described by 3 × 3 rotation matrices. Non-informative priors are identified and Metropolis-H...
Posterior predictive arguments in favor of the Bayes-Laplace prior as the consensus prior for binomial and multinomial parameters
Bayesian inference binomial distribution invariance noninformative prior
2009/9/24
It is argued that the posterior predictive distribution for the binomial
and multinomial distributions,when viewed via a hypergeometric-like representa-
tion, suggests the uniform prior on the param...
Bounded stopping time of some Bayes sequential tests for the t-test model
Bounded stopping time some Bayes sequential tests
2009/9/23
Bounded stopping time of some Bayes sequential tests for the t-test model。
A Method for Avoiding Bias from Feature Selection with Application to Naive Bayes Classification Models
feature selection optimistic bias naive Bayes models gene expression data
2009/9/22
For many classication and regression problems, a large number of
features are available for possible use this is typical of DNA microarray data
on gene expression, for example. Often, for computatio...
R. A. Fisher on Bayes and Bayes' Theorem
Ronald Fisher Thomas Bayes Pierre-Simon Laplace Dennis Lindley Inverse probability
2009/9/22
Ronald Fisher believed that Th theory of inverse probability is
founded upon an error, and must be wholly rejected. This note describes how
Fisher divided responsibility for the error between Bayes ...
Frequentist Bayes is Objective(Comment on Articles by Berger and by Goldstein)
coverage frequency probability objective Bayesian inference
2009/9/21
In this comment, I argue that Bayes procedures with good frequentist
properties are objective. I introduce the idea with a short play, followed by some
commentary.