搜索资源列表
bayesian
- 贝叶斯分类器设计,基于VC编写的,非常好
Bayes_classifier
- 贝叶斯分类器的设计实验,内有解释利于入门学习-Bayesian classifier design experiments, which help to explain the study entry
bayes
- 用matlab完成基于最小错误率的贝叶斯分类器的设计-Done with matlab error rate based on the minimum design of Bayesian classifier
question1
- 最小错误率的贝叶斯分类器设计matlab代码实现-Bayes minimum error rate classifier design matlab code
classification
- 在具有模式的完整统计知识条件下,按照贝叶斯决策理论进行设计的一种最优分类器。分类器是对每一个输入模式赋予一个类别名称的软件或硬件装置,而贝叶斯分类器是各种分类器中分类错误概率最小或者在预先给定代价的情况下平均风险最小的分类器。-In a model under the condition of complete statistical knowledge, in accordance with the Bayesian decision theory to design an optimal c
Bayes
- 贝叶斯分类实验,设计简单的线性分类器,了解模式识别的基本方法。掌握利用贝叶斯公式进行设计分类器的方法。-Bayesian classification experiment is designed to be simple linear classifier, know the basic methods of pattern recognition. Master the use of Bayesian classifier design formula method.
Bayes_classifier_useful
- 关于贝叶斯分类器设计的实验,适合入门,上一个传错了,抱歉-Bayesian classifier on the experimental design is suitable for entry, a mass is wrong, sorry
work_for_pattern_recognition
- 通过设计线性分类器;最小风险贝叶斯分类器;监督学习法分层聚类分析;K-L变换提取有效特征,设计支持向量机对给定样本进行有效分类并分析结果。-By designing a linear classifier minimum risk Bayes classifier supervised learning method hierarchical cluster analysis K-L transform to extract efficient features, designed to
bayes
- 贝叶斯分类器的设计与实现,非常好的应用程序,能够在其上面实现人脸识别-Bayesian classifier design and implementation of a very good application, face recognition can be achieved in the above
bayescode
- 一种自己设计的贝叶斯分类器,具有一定的参考价值-A kind of self-designed Bayesian classifier, with some reference value
FullBNT-1.0.4
- 比较全面的贝叶斯工具箱,包含贝叶斯分类器等的设计等-bayes tools box
bayes_fenleiqi
- 贝叶斯分类器设计。 对两组数据(学生的英语成绩)的分类-Bayesian classifier design. On two sets of data (student performance in English) classification
matlab
- 这是另一个matlab的贝叶斯分类器设计,可用作作业用-This is another matlab Bayesian classifier design can be used as operating with
bayes1
- 最小错误率贝叶斯决策 模式识别 贝叶斯分类器设计-Minimum error rate Bayesian decision pattern recognition Bayesian classifier design
bayes2
- 最小风险贝叶斯决策 模式识别 贝叶斯分类器设计-Minimum risk Bayesian decision pattern recognition Bayesian classifier design
bayes
- matlab基于最小错误率的贝叶斯分类器设计-Bayesian classifier design matlab minimum error rate
贝叶斯分类器设计
- 利用贝叶斯公式计算出其后验概率,即该对象属于某一类的概率,选择具有最大后验概率的类作为该对象所属的类。也就是说,贝叶斯分类器是最小错误率意义上的优化。
贝叶斯分类器
- 贝叶斯分类器设计,分参数已知和参数未知两种情况,含最大似然参数估计代码
贝叶斯分类器
- 该程序能够实现对两种样本进行贝叶斯分类,并且能够通过旋转观察两类的三维图,还能够画出超平面,更加直观的观察两类的分类。(The program can realize the Bayesian classification of two kinds of samples, and can be observed by rotating the 3D figure two class, also can draw a plane, the classification of the two cla
贝叶斯判决
- 假定某个局部区域细胞识别中正常w1和非正常w2 两类先验概率分别为: 正常状态:P(w1)=0.9 ; 异常状态:P(w2)=0.1 。 现有一系列待观察的细胞,其观察值为: -2.67 -3.55 -1.24 -0.98 -0.79 -2.85 -2.76 -3.73 -3.54 -2.27 -3.45 -3.08 -1.58 -1.49 -0.74 -0.42 -1.12 4.25 -3.99 2.88 -0.98 0.79 1.19 3.07 两类的类条件概率符合正态分布