搜索资源列表
Hierarchical
- 实现层次类聚的分类掘,运用C++实现,是一个控制台程序-implement of Hierarchical algorithm
cluster
- 本程序介绍了聚类分析的各种算法,包括层次、动态、模糊和遗传算法,对数值进行模式识别。-This procedure describes the various clustering algorithms, including the level of dynamic, fuzzy and genetic algorithms, pattern recognition value.
stockClustering
- 基于层次分析法的股票聚类方法,有具体数据,产生聚类效果图、簇间相似程度图-Stock-based clustering method of AHP, the specific data to produce the clustering effect diagram, the degree of similarity between the cluster diagram
tenmou
- 数学方法是部分子空间法,用MATLAB实现动态聚类或迭代自组织数据分析,AHP层次分析法计算判断矩阵的最大特征值。- Mathematics is part of the subspace, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Calculate the maximum eigenvalue judgment matrix of AHP.
piunou_v62
- 可实现对二维数据的聚类,毕设内容,高光谱图像基本处理,AHP层次分析法计算判断矩阵的最大特征值。- Can realize the two-dimensional data clustering, Complete set content, basic hyperspectral image processing, Calculate the maximum eigenvalue judgment matrix of AHP.
qantao
- 基于欧几里得距离的聚类分析,AHP层次分析法计算判断矩阵的最大特征值,matlab小波分析程序。- Clustering analysis based on Euclidean distance, Calculate the maximum eigenvalue judgment matrix of AHP, matlab wavelet analysis program.
bunkiu
- 基于K均值的PSO聚类算法,包含飞行器飞行中的姿态控制,如侧滑角,倾斜角,滚转角,俯仰角,AHP层次分析法计算判断矩阵的最大特征值。- K-means clustering algorithm based on the PSO, It comprises aircraft flight attitude control, such as slip angle, tilt angle, roll angle, pitch angle, Calculate the maximum eigenvalu
sy634
- AHP层次分析法计算判断矩阵的最大特征值,使用混沌与分形分析的例程,用MATLAB实现动态聚类或迭代自组织数据分析。- Calculate the maximum eigenvalue judgment matrix of AHP, Use Chaos and fractal analysis routines, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
nai_v87
- 是学习PCA特征提取的很好的学习资料,AHP层次分析法计算判断矩阵的最大特征值,包括AHP,因子分析,回归分析,聚类分析。- Is a good learning materials to learn PCA feature extraction, Calculate the maximum eigenvalue judgment matrix of AHP, Including AHP, factor analysis, regression analysis, cluster analysi
fk572
- 光纤陀螺输出误差的allan方差分析,AHP层次分析法计算判断矩阵的最大特征值,包括AHP,因子分析,回归分析,聚类分析。- allan FOG output error variance analysis, Calculate the maximum eigenvalue judgment matrix of AHP, Including AHP, factor analysis, regression analysis, cluster analysis.
Data-Mining
- 本论文在对各种算法深入分析的基础上,尤其在对基于密度的聚类算法、基于层次的聚类算法和基于划分的聚类算法的深入研究的基础上,提出了一种新的基于密度和层次的快速聚类算法。该算法保持了基于密度聚类算法发现任意形状簇的优点,而且具有近似线性的时间复杂性,因此该算法适合对大规模数据的挖掘。理论分析和实验结果也证明了基于密度和层次的聚类算法具有处理任意形状簇的聚类、对噪音数据不敏感的特点,并且其执行效率明显高于传统的DBSCAN算法。-Based on the analysis on clustering
bengtui_v75
- 实现了图像的加水印,去噪,加噪声等功能,基于欧几里得距离的聚类分析,AHP层次分析法计算判断矩阵的最大特征值。( Realize image watermarking, de-noising, plus noise and other functions, Clustering analysis based on Euclidean distance, Calculate the maximum eigenvalue judgment matrix of AHP.)