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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 ,
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%
Perceptron-twotextcategory.rar
- 感知器神经网络对简单的句子进行分类的程序, 可以扩展为对文章进行文本分类,Perceptron neural network for simple sentence classification procedures can be extended for text classification articles
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- 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
masotti_MLP_Classificazione
- 多层感知器的分类程序! -Multi-layer perceptron classification procedures!
fenlei
- 感知器分类，使用matlab-Single-layer perceptron classification
Conception
- 用vc写的神经网络感知器分类算法演示实现过程，效果不错。-Written by vc perceptron neural network classification algorithm implementation process demonstrated good results.
Perceptron
- matlab语言编写的iris数据的单层感知器分类-matlab data written in a single layer perceptron iris classification
pereceptron
- 感知器算法分类器，感知器是一种双层神经网络模型，一层为输入层，另一层具有计算单元，可以通过监督学习建立模式判别的能力-Perceptron Algorithm classifier, perceptron neural network model is a double layer of input layer, another layer with a calculation unit, you can determine by monitoring the ability of learni
zuoye2
- 感知器分类作业，将200个二维样本分成两类-Sensor classification operations, 200 two-dimensional samples divided into two categories
ganzhiqi
- 单层感知器分类和权值调整过程，学习率分别为0.01 0.05 0.1 0.5-Single layer perceptron device classification and weights to adjust the process
Linear
- 模式识别线性判别的程序实现，产生两个二维正态分布随机样本，分别进行Fisher线性分类和感知器分类。其中main.m是主函数，将三个程序放在同一文件夹中，运行main.m即可得到分类结果。-Pattern recognition linear discriminant program implementation, generate two-dimensional normal random sample, were Fisher linear classifier and Perceptron
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
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.)
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- 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)
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.)