贝叶斯算法，希望对大家有帮助。
朴素贝叶斯算法，可使用对象进行分类，通常是二进制类。
Naive Bayes is an algorithm that can be used to classify objects into usually binary categories.
文章以朴素贝叶斯算法为例，详细描述了性能预测模块的构建过程。
This paper takes Naive Bayes Classifier as an illustration to describe how to construct a prediction module in detail.
实验结果表明，与传统的朴素贝叶斯算法相比，该方法具有更好的性能。
The experimental results show that this algorithm has better performance when compared with traditional naive Bayesian algorithm.
最后提出一种改进的贝叶斯算法融合多视觉信息来估计驾驶员的疲劳程度。
Finally, we propose an improved Bayesian algorithm to estimate driver's fatigue over integration of visual information.
方法收集343种传染病症状、体征数据，运用贝叶斯算法建立分类模型。
Methods The data on 343 kinds of infectious disease symptoms, signs were collected and Bayesian classification model was constructed.
一个简单的机器学习算法，朴素贝叶斯算法可以把正规邮件从垃圾邮件里面分离出来。
A simple machine learning algorithm called naive Bayes can separate legitimate email from spam email.
为实现电缆故障定位系统的参数估计，提出了一种用于模型参数估计的改进贝叶斯算法。
In order to implement the parameter estimate in cable fault location system, an improved Bayes algorithm used for Model parameter estimate is proposed in this paper.
在垃圾邮件分类和朴素贝叶斯算法研究的基础上，提出了基于用户知识的贝叶斯分类算法。
An user knowledge based na? Ve bayes classifier was proposed in order to conquer the problem that most of the E-mail is unstructured and need users decoding.
基于内容的贝叶斯算法在垃圾邮件处理上表现出了较高的准确度，因此受到了广泛的关注。
Bayesian algorithm based on the content filter showed a high degree of accuracy when filter the spam therefore it has received extensive attention.
朴素贝叶斯算法是一种简单而高效的分类算法，但是它的条件独立性假设影响了其分类性能。
Naive Bayes algorithm is a simple and effective classification algorithm. However, its classification performance is affected by its conditional attribute independence assumption.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
在客户支持方面，贝叶斯过滤（Bayesian Filtering）算法会阻击所有spam，让email能够准确投递到相应的部门。
On the customer support side, a Bayesian Filtering algorithm zaps spam and turns email into trackable cases routed to the correct department.
为了解决该方法存在的训练数据集问题，本文改进了现有的贝叶斯分类算法，提出了利用未标记数据提高贝叶斯分类器性能的方法。
In order to solve the problem existing in training data sets, present Bayes algorithm is im - proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.
这种新的贝叶斯滤波算法是粒子滤波器与划分采样技术和假设计算的有机结合。
The proposed algorithm is a combination of the partition sampling technique and hypothesis calculations with the particle filter.
在大规模基因表达谱的数据分析中引入了一种全新的基于贝叶斯模型的聚类算法。
A novel clustering algorithm based on Bayesian model was introduced into the analysis of large-scale gene expression profiles.
最后介绍了贝叶斯过滤算法反垃圾邮件的基本步骤。
Finally introduced the fundamental step of filtering spam mail with Bayesian algorithm.
首先介绍了贝叶斯抽样方案的原理，给出批量较小时这类方案的简单精确算法。
This theory of Bayesian sampling plans, Then gives simple and exact algorithms of this kind of plans for small lot sizes.
将贝叶斯优化算法(BOA)引入到协同攻击优化领域中。
The Bayesian Optimization Algorithm (BOA) was introduced to tackle the coordination attack problem.
针对潜在语义分析（LSA）模型的权重更新问题，提出了一种基于贝叶斯理论的自适应权重更新算法ALSAB。
To the weight update of Latent Semantic Analysis(LSA)model, this paper proposes an adaptive weight update algorithm based on Bayesian theory(ALSAB).
本文在分析了多种贝叶斯网络结构学习算法的基础上，并且根据水电仿真的应用背景，提出了一种根据多专家提供的规则库进行贝叶斯网络结构学习的新算法。
The Thesis analyses many kinds of Algorithm about Bayesian network structure learning, and then Setting-up a new Algorithm about structure learning Foundation on hydro-electrical simulation system.
例如，我们使用GPS和贝叶斯决策理论算法，分别构建了预测蛋白质磷酸化位点的GPS和PP SP网站。
For example, we construct GPS and PPSP for phosphorylation site prediction, based on GPS and Bayesian Decision Theory algorithms, respectively.
研究了基于贝叶斯网络的推理模型以及基于此模型的推理算法。
The inference model based on Bayesian Network is discussed and the algorithm based on the model is presented.
我的主要工作是把粒子滤波算法引人到非线性贝叶斯动态模型中来，对非线性模型进行了模拟。
My main work is applying the particle filter algorithm to random simulate the non-linear Bayesian dynamic models.
首先，我们综述了基于贝叶斯阴阳机和谐学习原则的自动模型选择学习算法。
First, we summarize some amS learning algorithms on Gaussian or finite mixture based on the Bayesian Ying-Yang (BYY) harmony learning principle.
基于秩- 1更新，提出了稀疏贝叶斯学习算法(SBLA)。该算法具有较低的计算复杂度和较高的稀疏性，从而适合于求解大规模问题。
Based on a rank-1 update, we propose sparse Bayesian Learning Algorithm (SBLA), which has low complexity and high sparseness, thus being very suitable for large-scale problems.
讨论了离散贝叶斯分类算法之后，推导了离散贝叶斯分类器的分类误差估算公式。
The algorithm of discrete Bayes classifier is proposed. Then, formulas for estimating classifying error of Bayes classifier are deduced.
针对舰船战场损伤评估的多元信息特点，建立了在观测操作条件下的舰船战场损伤评估的贝叶斯网络推理算法。
Object to the multi sensors character in warship battle damage assessment, a Bayesian net inference arithmetic is up forward considering observation operation.
针对舰船战场损伤评估的多元信息特点，建立了在观测操作条件下的舰船战场损伤评估的贝叶斯网络推理算法。
Object to the multi sensors character in warship battle damage assessment, a Bayesian net inference arithmetic is up forward considering observation operation.
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