搜索资源列表
Adaboost-detection
- 基于ADABOOST的人脸检测程序，有分类器训练和测试-face detection based on adaboost
fenleisuanfa
- 分别采用感知机算法、最小平方误差算法、线性SVM算法设计分类器，分别画出决策面，并比较性能。-Perceptron algorithm were used, the least square error algorithm, linear SVM classifier algorithm, respectively, making face paint, and compare performance.
ensembles_pca_svm_new10v
- pca做特征降维，然后进行特征空间随机分割构造多个svm分类器，并行处理，对样本进行分类，基于特征空间的svm多分类器-using pca reduce feature dimension,split feature space and then randomly divided over svm classifier construction, parallel processing, the samples were classified, based on multi-feature sp
K-mean
- 最近邻分类器是一个用来聚类的算法，可以用来对iris数据进行聚类-k-means is a neanest alogorim
SVM13
- SVM神经网络中的参数优化---提升分类器性能 -SVM parameters optimization of neural network classifiers to enhance the performance---
prtools
- SVDD（无监督）分类器中所用到的程序集-SVDD classifier used in the assembly
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
感知分类器的MATLAB仿真源代码
- 感知器数据分类 MATLAB源代码实现 机器学习(classification machine learning)
RANSIC1
- ransac分类器，应用于二维点，自带检测算法(RANSAC classifier, applied to two-dimensional points, comes with detection algorithms)
boosting_demo
- boosting算法用于集成学习，包含多种弱分类器(Boosting algorithm is used for ensemble learning, and it contains many weak classifiers)
knn_toy
- 这是一个K近邻分类器，手动编写的一个较为简单的实现。(K nearest neighbor classifier)
test2-BP
- 采用BP神经网络设计男女生分类器。采用的特征包括身高、体重、是否喜欢数学、是否喜欢文学、是否喜欢运动共五个特征，BP神经网络包含一个隐层，隐层结点数为5。(Using BP neural network to design a classifier for male and female students. The features include height, weight, whether they like mathematics, whether they like literatur
模式识别
- 简单的贝叶斯分类器，实现基于身高体重的男女性别分类(Simple Bias classifier)
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)
线性分类器
- 该程序能够实现对于一个样本完成感知机，最小二乘法，凸优化方法解决SVM和matlab自带函数解决SVM的四种程序，并且通过修改部分参数可以完成不同效果。(The program can be achieved for a complete sample perceptron, least squares method, convex optimization method to solve SVM and MATLAB with four program function to solve th
kernelBP_chol
- 针对图像的基于核置信传播的分类器，具有收敛速度快，精度高的优点。(This is a sample code for Kernel Belief Propagation Classifier for images.)
svm参数优化
- 采用svm来做分类，一般能得到较满意的结果，但用svm做分类预测时需要调节相关的参数才能得到比较理想的预测分类准确率，那么svm的参数该如何选取？该程序主要说明如何更好地提升分类器性能。(Use svm to do the classification, the general can get more satisfactory results, but when using svm to do classification prediction need to adjust the relev
贝叶斯
- 贝叶斯分类器的分类原理是通过某对象的先验概率，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(The classification principle of Bias classifier is to calculate the posterior probability by using Bias's formula through the prior probability of an object, that is, the proba
Bayes classifier
- 基于贝叶斯分类器的数据处理与MATLAB实现(Data processing based on MATLAB implementationof Bayes classifier)
随机森林分类器
- 对提取好的n维特征，实现随机森林分类器分类。(For the extraction of good characteristics, the realization of random forest classification)