搜索资源列表
c02
- [demo.rar] - 增值税发票抵扣联字符识别中的图像倾斜校正方法,很有用 [2007012218032016052.rar] - 目前紧紧支持24种验证码的识别,后续版本将会慢慢加入更多可识别的格式。 [OCR.rar] - OCR光学字符识别代码,思想是背景16值变化,提供勾,圈,叉识别 [javawllt.rar] - 用JAVA编译的局域网聊天程序 v 1.0 ,此聊天程序为学习java语言而开发的 [MySoft.rar] - 一种利用硬盘序列号对
NeuralNetwork_BP_Classification
- RBF神经网络的一个样本分类的例子,很简单,懂Matlab基础的就能看明白。-RBF neural network classification of a sample of examples of very simple, based on Matlab understand能看明白.
etos-1.1.2.tar
- 用于脑电信号的检查和分类 高度集成化,简单容易-Used for EEG examination and classification of highly integrated, simple and easy to
PCA_Fisher
- Matlab写的fisher 分类器,很简单适合初学者,体验机器学习的过程-Fisher Linear Discriminant Analysis in Matlab。It fit the people who learning the Machine Learning at first time.
k-mean
- K均值(用matlab实现花的分类,附注释,程序简单)-K-means (machine learning job classification flowers)
BayesClassification-Matlab
- 简单的贝叶斯分类器的Matlab实现,并提供了三个实例-Simple Bias classifier Matlab implementation, and provides three examples
orin-svm
- Matlab 中的 SVM(支持向量机)分类的简单演示程序-SVM Sample for Matlab
knn-softsvm
- knn,最小二乘,softsvm分类器的matlab实现,以及简单的交叉验证等-knn, least squares, soft svm classifier matlab implementation, and simple cross-validation, etc.
perceptron
- 关于分类的自己写的感知机matlab 源程序,比较简单。-Write your own perception on the classification of machine matlab source, it is relatively simple.
BP
- BP算法的MATLAB实现,很简单的分类小程序(BP algorithm MATLAB implementation, the small classification procedure is very simple)
Rosenblatt_Perceptron
- 用MATLAB实现一个简单的分类器,对线性的点进行简单的分类。(Using MATLAB to implement a simple classifier, a simple classification of linear points.)
code
- matlab单层神经网络实现与逻辑,感知器是一种最简单的神经网络,可以解决最简单分类问题。在本经验中,利用了MATLAB代码简单实现了一个单层神经网络的感知器,对“与”逻辑运算进行了训练和学习,以便我们深入地了解感知器的构造。(Implementation and logic of MATLAB single layer neural network)
k-nn
- k-nn算法 K-NN算法 ( K Nearest Neighbor, K近邻算法 ), 是机器学习中的一个经典算法, 比较简单且容易理解. K-NN算法通过计算新数据与训练数据特征值之间的距离, 然后选取 K (K>=1) 个距离最近的邻居进行分类或者回归. 如果K = 1 , 那么新数据将被分配给其近邻的类.(k-nnK - NN algorithm (K on his Neighbor, K Nearest Neighbor algorithm), is a classical al
Adaboost
- 用MATLAB实现Adaboost分类算法,只是一个简单的功能(Using MATLAB to implement Adaboost classification algorithm, it is just a simple function)