搜索资源列表
pattern_recognition
- 模式识别中的几个常用算法，包括ISODATA算法、K－均值算法、感知器算法、LMSE最小误差、贝耶斯分类。-pattern_recognition have some usual algorithm,including ISODATA algorithm,K-means algorithm,apperceive algorithm ,
PerceptionApproach
- 模式识别的经典算法之一，感知器算法，用来对模式进行分类，采用matlab编写。-the classic pattern recognition algorithm, perception algorithm, the model used for classification, prepared using Matlab.
percept1
- 多个感知器神经元的分类问题 ％四类输入向量-many neurons in the classification of four input vector%
pointsclassify
- 用于模式识别分类，有C均值算法、HK算法以及感知器算法-for the classification, C-means algorithm, HK algorithm and Perceptron Algorithm
bp_feel_classification
- 此为BP感知神经分类器,自己写的.有须要的请下载,很不错的.-this perception of BP neural classifier himself wrote it. The need to please download, very good.
percep
- 感知器网络的几个例子 都试过的，不错 包括分类 学习 等-perceptron network had tried several examples, including a breakdown good learning
Perceptron_example2
- 采用单一感知器神经元解决一个简单的分类问题，将四个输入矢量分为两类，其中 ％ 两个矢量对应的目标值为1，另两个矢量对应的目标值为0-single perceptron neural yuan to solve a simple classification, four input vectors are divided into two categories. 2% which the vector corresponding to a target value, and the other
Perceptron_example6
- 分析单层感知器无法解决线性不可分输入矢量的分类问题-analysis of single-layer perceptron unable to solve the non-linear input vector classification
percep3
- 一个感知器的网络训练模型,给出了分类曲线
ganzhi
- 神经网络感知器做的分类器的源码，适合神经网络初学者
NNLM1
- 神经网络与机器学习第一章：感知器分类半月形数据-Neural Networks and Machine Learning Chapter I: Classification meniscus sensor data
分类器识别
- 基于halcon，运用多层感知的分类器字符识别，和颜色识别、(Based on Halcon, multilayer perceptron classifier is used for character recognition and color recognition,)
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
shiyan4
- 解决非线性多类别分类问题，利用实际数据进行分类处理。(Solving nonlinear multi class classification problem, using actual data for classification processing.)
2
- 通过随机产生高斯分布数据，来对数据进行分类。(The data are classified by random generation of gaussian distribution data.)
svm
- 支持向量机由Vapnik首先提出，像多层感知器网络和径向基函数网络一样，支持向量机可用于模式分类和非线性回归，该程序主要实现svm的分类和回归功能。(SVM was first proposed by Vapnik. Like multilayer sensor network and radial basis function network, SVM can be used for pattern classification and non-linear regression. The p
matlab脚本文件
- 输入两组变量即可进行系统优化迭代，选择最佳变量(The system optimization iterations can be carried out by the input of two groups of variables, and the optimal variables are selected)
perception
- 多分类的感知器算法，包括Ho_Kashyap的mse实现(Multiple classification of perceptron algorithms, including the MSE implementation of Ho_Kashyap)
MLP_iris
- 一个简单的多层感知器实现鸢尾花数据的分类的代码(use mlp to realize the classification of Iris dataset)
鸢尾花分类
- 使用四种方法进行鸢尾花分类：最小距离分类器，K 近邻法，感知器，Fisher 准则。(Four methods are used to classify iris: minimum distance classifier, K-nearest neighbor method, perceptron and Fisher criterion.)