搜索资源列表
svm
- 用MATLAB编写的svm源程序，可以实现支持向量机，用于特征分类或提取-MATLAB svm prepared by the source, can achieve a support vector machine for the feature classification or extract
复杂网络提取图像边缘特征
- 使用复杂网络提取图像边缘特征并进行识别的源代码，采用PCA_LDA算法对特征进行降维分类识别，识别效率很高。鲁棒性好
PCA_LDA.rar
- 《机器学习》课上的作业，PCA和LDA降维，尽管网上很多，但很少注释，另外细节上也没注意。这里有很详细的注释。另外还附上一个Naive贝叶斯分类器，大家可以作比较。附带的图像包是OLR人脸。ReducedDim为想要提取的特征数，不是百分比！," Machine learning" classes on the homework, PCA and LDA dimensionality reduction, even though a lot of online, but f
knn
- knn-K近邻法实现两分类的函数代码，输入为两类的样本特征，和待测试的样本向量，输出为分类结果。-knn-K nearest neighbor method to achieve the two categories of function code, enter the characteristics of two types of samples, and samples to be tested vector, the output for the classification.
贝叶斯分类算法
- 贝叶斯分类算法程序，matlab，和那好很好很
MATLA+svm
- 用MATLAB编写的svm源程序，可以实现支持向量机，用于特征分类或提取-SVM prepared using MATLAB source code, you can achieve the support vector machine for feature classification or extraction
11
- 神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例-Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input
m10_9
- 一维自组织特征映射网络对输入向量空间进行识别分类-One-dimensional self-organizing feature map network input vector space to identify categories
WeightedFeature
- 给出两个加权特征，一个是加权笔画密度特征，另外一个是加权外围特征，用一级汉字实验结果表明，这两个特征具有很强的汉字信息，能很好的为模式分类提供有效的特征- Give out two weighted feature abstraction method One is the weighted stroke density feature , the other is the weighted Periphery feature.The reslut of experiment on the f
featureselection
- 模式分类中的特征选择,希望大家可以参考一下.-Pattern Classification in feature selection, hope that we can reference.
ar_dct_lda
- AR人脸库进行DCT变换，然后使用Fisher discriminant analysis 进行特征提取，使用cos分类器进行人脸分类。-AR Face Database for DCT transform, and then use the Fisher discriminant analysis feature extraction, using cos classifier for human face classification.
patternrecognitionfuzzyclassifiy0912
- 模式分类，提取的新特征，包括熵和尺寸特征，可分性好效果明显-pattern recognition ,new feature incuding entropy and size feature, better performance
NB
- 特征之间非独立的有监督朴素贝叶斯分类算法。参数估计，输入训练集和测试集，得到分类结果和分类准确率-NB
abbr_b11a93e762f6958bb657c1ad7c58d2b5
- 用MATLAB编写的svm源程序，可以实现支持向量机，用于特征分类或提取-MATLAB svm prepared by the source, can achieve a support vector machine for the feature classification or extract
svm
- SVM源程序，可以用来进行特征分类或提取 -MATLAB svm prepared by the source, can achieve a support vector machine for the feature classification or extract
svm
- 本程序包括：论文SVM 用于基于块划分特征提取的图像分类，和相应的matlab实现其中图像划分以及特征提取、聚类均利用matlab6.5完成。 -The procedures include: paper by SVM for feature extraction based on block classification, and the corresponding realization of one image into matlab, and feature extraction,
case1
- BP神经网络的数据分类-语音特征信号分类-BP Neural Network for Data Classification- Classification of speech feature signals
BP神经网络的数据分类-语音特征信号分类
- BP神经网络的数据分类-语音特征信号分类(BP neural networks for data classification -- speech feature signal classification)
SVM
- SVM分类器的matlab实现，针对提供的花的特征分类，并交叉验证(The matlab implementation of SVM classifier aims at providing the feature classification of flowers and cross validation)
svm分类预测
- wine的数据来源是UCI数据库，记录的是在意大利同一区域里三种不同品种的葡萄酒的化学成分分析，数据里含有178个样本，每个样本含有13个特征向量（化学成分），每个样本的类别标签已给，该程序主要实现意大利葡萄酒种类识别。(The data source for wine is the UCI database, which records the chemical composition of three different varieties of wines in the same area