Bayesian inference

基本解釋

The most common statistical approach is called bayesian inference and is explained in detail in another IBM developerWorks article (see Resources).
最常見的統(tǒng)計方式稱為貝葉斯推理，更詳細的內容，可以參閱 IBM developerWorks 的另一篇文章（參見參考資料）。
Bayesian inference has also gained prominence in e-mail spam-fighting, and in non-spam-related areas such as customer affinity engines (or, commercial recommendation engines).
貝葉斯推理在對付電子郵件中的垃圾信息以及其他與垃圾信息不相關的領域（比如客戶親和力引擎，或商業(yè)推薦引擎）均有突出的表現(xiàn)。
The algorithm handles uncertain information with Bayesian inference, giving a quantitative evaluation of the security state of a system and eliminating false alarms effectively.
算法用貝耶斯推理處理不確定信息，量化地評估系統(tǒng)安全狀態(tài)，并且有效地消除誤報。

貝葉斯推理
This paper proposes a new image segmentation algorithm based on watershed transformation combined color information and uses Bayesian inference on this watershed image.
提出了一個結合彩色信息的分水線圖像分割方法,在LUV顏色空間的分水線圖像上,使用貝葉斯推理的圖像分割方法。
貝葉斯推斷
A Bayesian inference is based on posterior densities of the parameters, namely for the j-th parameterθ_j the conditional density .
一個貝葉斯推斷是基于后驗密度函數(shù)的參數(shù)的,也就是說對第j個參數(shù)θ_j的條件密度為。
貝斯推理

貝葉斯推斷
By the time-discretization approach, this paper derives a stochastic difference equation from the geometric mean-reversion process and then a nonlinear regression model is established. By this way, the paper obtains the distribution and estimation for each parameter by Bayesian inference.
針對連續(xù)幾何均值回復模型,通過時間離散化導出對應的隨機差分方程,從而得到一個非線性回歸模型,進而利用貝葉斯推斷得到各個參數(shù)的估計及后驗分布。
bayes估計