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这是《数据挖掘原理与应用—SQL Server 2008数据库》的随书SQL语句、源代码和Excel范例文件,基于DMX,代码主要包括对SQL Server 2008和Excel 2007中已经集成好的数据挖掘算法的应用, 如贝叶斯聚类、决策树、时序、聚类、序列聚类、关联规则、神经网络、逻辑回归、OLAP立方体的等算法,具有极高的使用价值。-This is the " Principles and Applications of data mining-SQL Server 2008 d
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数据挖掘算法源码,有聚类算法、分类算法、神经网络分类算法-Source of data mining algorithms, a clustering algorithm, sorting algorithm, neural network classification algorithm
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C-均值聚类
BP神经网络信号分析与处理方法,对模拟产生的数据样本进行训-C-means clustering analysis and BP neural network signal processing method, the simulated data generated training samples
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Neural Network OCR.
There are many different approaches to optical character recognition problem. One of the most common and popular approaches is based on neural networks, which can be applied to different tasks, such as pattern recognition, time
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LVQ算法( Learning Vector Quantization,学习矢量量化网络)是一种一种基于模型(神经网络)的方法,本实验要实现的是对LVQQ改进的聚类方法——MLVQ(闫德勤等人提出)。该方法法克服了LVQ算法对初值敏感的问题与广义学习矢量量化(GLVQ)网络算法性能不稳定的缺点。(附文章)
-LVQ algorithm (Learning Vector Quantization, learning vector quantization) is a based on the
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k均值聚类算法,初始随机给定k个簇中心,根据邻近原则,把待分类的样本点分到各个簇。-k-means clustering algorithm,which is applied in RBF neural network.
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用自组织特征映射神经网络对Iris数据集进行分类,我用神经网络工具箱编写了个简单的程序,实现iris的分类。-Using self-organizing feature map neural network examples of clustering Iris data set classification, I use neural network toolbox to write a simple program, realize the classification of Iris.
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用神经网络中的kohonen网络来做聚类-Using neural networks do kohonen network clustering
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基于聚类的径向基神经网络的设计算法,采用的是K均值聚类。实现函数拟合!-The design algorithm of radial basis function neural network based on clustering, using the K mean clustering. Realize the function fitting!
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GLVQ neural network, this method is suitable for the two classification results of data processing
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神经网络聚类的matlab实现,内含多个文件-Matlab neural network clustering to achieve
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graynet_prediction algorithm文件夹为灰色神经网络的预测算法—订单需求预测
kohonen_cluster文件夹为网络的聚类算法—网络入侵聚类-graynet_prediction algorithm folder is gray neural network prediction algorithm- order demand forecast
kohonen_cluster folder is clustering algorithm network-
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这是一个关于Kohonen神经网络的小程序,主要实现了利用神经网络进行聚类的功能,经测试具有良好效果-This is a small program on Kohonen neural network, the main achievement of the neural network clustering feature has been tested with good results
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BP(Back Propagation)网络是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。
BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。
它的学习规则是使用最速下降法,通过反向传播来不断调整网络的权值和阈值,使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层(input)、隐层(hide layer)和输出层(output layer)。
通过对信息的提取以及
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关于神经网络控制,仿真效果非常好,基于欧几里得距离的聚类分析。- On neural network control, Simulation of the effect is very good, Clustering analysis based on Euclidean distance.
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基于欧几里得距离的聚类分析,关于神经网络控制,用MATLAB实现动态聚类或迭代自组织数据分析。- Clustering analysis based on Euclidean distance, On neural network control, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
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基于人工神经网络的常用数字信号调制,可实现对二维数据的聚类,加入重复控制。- The commonly used digital signal modulation based on artificial neural network, Can realize the two-dimensional data clustering, Join repetitive control.
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基于欧几里得距离的聚类分析,BP神经网络的整个训练过程,详细画出了时域和频域的相关图。- Clustering analysis based on Euclidean distance, The entire training process BP neural network, Correlation diagram shown in detail the time domain and frequency domain.
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实现用神经网络的聚类问题,采用了PSO进行优化,引入了浮动质心的概念-Implement clustering and neural network
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BP神经网络用于函数拟合与模式识别,用MATLAB实现动态聚类或迭代自组织数据分析,主同步信号PSS在时域上的相关仿真。- BP neural network function fitting and pattern recognition, Using MATLAB dynamic clustering or iterative self-organizing data analysis, PSS primary synchronization signal in the time domai
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