Description: fisher判别函数分类的实现，简单易懂，不是水准。很好的解决了我的问题。-fisher discriminant function classification realize, easy-to-read, not the standard. Very good solution to my question. Platform: |
Size: 527360 |
Author:陈丁雷 |
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Description: 这是一各关于线性判别函数分类的MATLAB程序，希望对大家的学习有所帮助-This is the one on the linear discriminant function classification MATLAB program, and they hope to learn from everyone Platform: |
Size: 1024 |
Author:王霞 |
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Description: 產生k個d維的常態分布樣本，產生某個事前機率為P(wi)的常態分布的discriminant
function，計算任兩點間的Euclidean distance及Mahalanobis distance
-Generated k-d-dimensional normal distribution of samples to generate a prior probability P (wi) of the normal distribution of the discriminant function, calculated between any two points in Euclidean distance and Mahalanobis distance Platform: |
Size: 38912 |
Author:amy |
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Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
Size: 4271104 |
Author:查日东 |
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Description: function [clusters,c,F]=fisher_classify(A,B,data)
fisher判别法程序
输入A、B为已知类别样本的样本-变量矩阵，data为待分类样本
输出C为判别系数向量
-function [clusters, c, F] = fisher_classify (A, B, data) fisher discriminant method procedures input A, B for a sample of known types of samples- variable matrix, data to be classified as output samples for discriminant coefficient vector C Platform: |
Size: 1024 |
Author:王晶 |
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Description: This function calculate the performance, based on Bayes theorem, of a clinical test. The input is based on a 2x2 matrix (true positive, false positives false negative, true negatives).
The Outputs are:
- Prevalence of disease
- Test Sensibility with 95 confidence interval
- Test Specificity with 95 confidence interval
- False positive and negative proportions
- Youden s Index
- Matthews Correlation Coefficient
- Number needed to Diagnose (NDD)
- Discriminant Power
- Test Accuracy
- Mis-classification Rate
- Positive predictivity
- Negative predictivity
- Positive Likelihood Ratio
- Negative Likelihood Ratio
- Test bias
- Diagnostic odds ratio
- Error odds ratio-This function calculate the performance, based on Bayes theorem, of a clinical test. The input is based on a 2x2 matrix (true positive, false positives false negative, true negatives).
The Outputs are:
- Prevalence of disease
- Test Sensibility with 95 confidence interval
- Test Specificity with 95 confidence interval
- False positive and negative proportions
- Youden s Index
- Matthews Correlation Coefficient
- Number needed to Diagnose (NDD)
- Discriminant Power
- Test Accuracy
- Mis-classification Rate
- Positive predictivity
- Negative predictivity
- Positive Likelihood Ratio
- Negative Likelihood Ratio
- Test bias
- Diagnostic odds ratio
- Error odds ratio Platform: |
Size: 3072 |
Author:Rafal |
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Description: 利用matlab实现的数值型贝叶斯分类器的源代码，可以用来分类或识别，很值得收藏-Using matlab to achieve numerical Bayesian classifier source code can be used to classification or identification, it is worthy of collection Platform: |
Size: 4096 |
Author:satanwings |
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Description: 使用Fisher 现行判别函数对给定的样本进行训练，对于两类，Fisher线性判别函数很好做，就是 w = Sw (m1 - m2), 其中：Sw为总类内离散度矩阵， m1, m2, 为两个模式类的均值-Fisher discriminant function using the current sample of a given training for two, Fisher linear discriminant function is well done, that is, w = Sw ' (m1- m2), where: Sw of the total within-class scatter matrices, m1, m2, the mean value for the two pattern class Platform: |
Size: 1024 |
Author:shihao |
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Description: 本文采用最小平方误差准则(MSE准则)通过训练样本集建立线性判别函数，并用线性判别函数去判断测试集。
数据集报告：
1、男女生
2、sona
3、ups-In this paper, the least square error criterion (MSE criterion) the training sample set by a linear discriminant function, and a linear discriminant function to determine the test set. Data Set Report: 1, boys and girls 2, sona 3, ups Platform: |
Size: 2048 |
Author:李碧聪 |
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Description: 贝叶斯分类器实现多类识别，主要用于两类的识别-BAYES_CLASSIFIER function calculates the discriminant functions for
two classes. Platform: |
Size: 1024 |
Author:xingtao |
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Description: 在模式识别中线性判别函数的MATLAB实现，与程序分析-Linear discriminant function in pattern recognition of the MATLAB implementation, and program analysis Platform: |
Size: 525312 |
Author:tanliguo |
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Description: 利用聚类、和判别函数方法，设计 MATLAB GUI对路标进行提取，得到了高质量的分类结果。-useing Clustering and Discriminant function to recognize the Sign, the method is robust to the disturbance. Platform: |
Size: 1262592 |
Author:ljhui |
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Description: 该文件夹中有六个M文件，说明如下：
boundary_extraction.m : 目标区域边界抽取主函数，其中调用ostu、four_neighbor、eight_neighbor、globe_graph
otsu.m : 类判别分类法（otsu全局二值化算法）
four_neighbor.m : 四邻域法边界抽取
eight_neighbor.m : 八邻域法边界抽取
globe_graph.m : 全局检测法边界抽取
area_peri.m : 目标区域周长计算主函数，调用ostu
4A.bmp
face.bmp
gun.bmp : 原始灰度图片
PeriAnalysis.txt : 记录了实验过程中目标区域的总数和各自的周长
实验结果文件夹 : 保存了实验过程中生成的图像和程序流程图-The folder has six M-file, as follows: boundary_extraction.m: the main function of the target area boundary extraction, which calls ostu, four_neighbor, eight_neighbor, globe_graph otsu.m: class discriminant classification (otsu global binarization algorithm) four_neighbor . m: neighbors-domain method boundary extraction eight_neighbor.m: eight neighborhood boundary extraction method globe_graph.m: Global detection boundary extraction area_peri.m: calculate the circumference of the main function of the target area, call ostu 4A.bmp face.bmp gun.bmp : The original grayscale pictures PeriAnalysis.txt: recorded during the experiment the total number of the target area and their perimeter results Folder: to save the images generated during the experiment and the program flow chart Platform: |
Size: 254976 |
Author:许胜强 |
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Description: 该程序为matlab程序，共有三个文件，dataC.m为程序入口，实现功能对50组数据用k均值算法进行分类，再对40组数据用感知器算法训练，然后用训练得到的判别函数对剩下10组数据分类，最后与原始分类做差比较，若分类无误，则全显示为0.-Matlab program on the program, a total of three files dataC.m for program entry features 50 sets of data with k-means algorithm to classify 40 sets of data with the training of the perceptron algorithm, and then using the trained discriminant function The remaining 10 sets of data classification, and finally with the original classification poor comparison, if the classification is correct, then the whole show. Platform: |
Size: 3072 |
Author:阿书 |
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Description: 一种二次判别函数在MATLAB环境中的实现与应用-A quadratic discriminant function in MATLAB Implementation and Application of Platform: |
Size: 9216 |
Author:吴建章 |
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Description: 本实验的目的是学习Parzen窗估计和k最近邻估计方法。在之前的模式识别研究中，我们假设概率密度函数的参数形式已知，即判别函数J(.)的参数是已知的。本节使用非参数化的方法来处理任意形式的概率分布而不必事先考虑概率密度的参数形式。在模式识别中有躲在令人感兴趣的非参数化方法，Parzen窗估计和k最近邻估计就是两种经典的估计法。(The purpose of this experiment is to study the Parzen window estimation and the k nearest neighbor estimation method. In previous pattern recognition studies, we assume that the parameter form of the probability density function is known, that is, the parameter of the discriminant function J (...) is known. This section uses nonparametric methods to handle any form of probability distribution without having to consider the parameter form of probability density. In pattern recognition, there are hidden nonparametric methods that are interesting. Parzen window estimation and K nearest neighbor estimation are two classical estimation methods.) Platform: |
Size: 2048 |
Author:bss
|
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