搜索资源列表
k-means-original
- k-menas算法是最简单的聚类算法，算法内详细介绍了各个函数和功能，对初学者很有借鉴意义-K-MEANS algorithm is one of the most simple clustering algorithm, there are different form, this is one of them, a reference for beginners
kmeans
- k-means算法是文本聚类经典算法，也是数据挖掘十大经典算法之一。k-means算法Java实现。-k-means algorithm is a classical algorithm text clustering, data mining is one of the ten classic algorithms. k-means algorithm is implemented in Java.
knn_java
- java写的k最邻近算法，是数据挖掘的基本算法之一。-Java write the k nearest neighbor algorithm, is one of the basic algorithm of data mining.
EM
- EM算法是数据挖掘算法之一，有兴趣的可以来学习。-EM algorithm is one of data mining algorithms, interested can learn.
Rtree
- R树是GUTTMAN于1984年提出的最早支持有序扩展的对象存取方法之一，也是目前应用最为广泛的一种空间索引结构，该资料为其的应用。-R tree is one of GUTTMAN first proposed in 1984 to support an orderly expansion of the Object Access Method, is currently the most widely used of a spatial index structure for the app
question-one
- K-means进行文字图像分类，基础方法一-exploit K-means to classify the graphs
LDM
- 对SVM分类方法进行的一种改进方法。将其中的margin改变。-SVM classification method for an improved method. The margin will be one change.
SVM_regression_1001
- 一种可以择优选择参数的SVM拟合回归程序，通过for循环，可以调节参数，调出误差最小的参数设置。有时候，默认的参数也会有很不错的精度。-One can choose the best parameters of the SVM fitting regression procedures, through the for cycle, you can adjust the parameters, minimize the error of the parameter settings. Somet
FCBF
- This a one of the data mining algorithm completly made by me. This is based on feature subset selection. One of the popular algorithm of feature selection named Fast Correlation based feature selection algorithm(FCBF).It s complete code is here with
TreeGrowthForIris
- 数据挖掘十大算法之一，决策树归纳算法，用于iris.data数据，能够实际运行-Data mining is one of ten algorithms, decision tree induction algorithm for iris.data data, can actually run
GUI-toolbar-and-tips
- GUI工具栏及其使用技巧，这里给了两个具体实例和其中一个画图过程。-GUI toolbar and tips, here to give two concrete examples and one drawing.
K_Means-algorithm
- very useful matlab code for K_Means Algorithm it can be use after change the given input data or use the original one that i provided with the code you can start by run K_Means_Clustering.m
multi-dimensional-particle
- 一维及二维数据粒子算法寻优,包括1）二维粒子算法参数寻优-替代网格寻优；2）一维数据粒子算法寻优（极值）。- One dimensional and two dimensional data particle algorithm optimization, including 1) two dimensional particle algorithm parameter optimization- alternative grid optimization 2) one dimens
Apriori
- Apriori算法是一种最有影响的挖掘布尔关联规则频繁项集的算法。其核心是基于两阶段频集思想的递推算法。- Apriori algorithm is one of the most influential mining Boolean association rules frequent itemsets algorithm. Its core is based on a two-stage frequency set recursive algorithm thought.
DataTest
- 统计一亿个IP中每个出现的次数，找不到大数据之类的分类，只能选择数据挖掘-Statistics IP in one hundred million times each appears, can not find such a large data classification, data mining can only choose
CHI
- 计算特征的卡方校验值，最后一列为样本标签，输出为特征的卡卡校验值及对应的特征序列号-The chi-square calculate checksum feature, the last one as a sample label, the output characteristics of the card verification value and the corresponding serial number feature
cengcijvlei
- 层次聚类分析也称系统聚类法或分级聚类法，是实际工作中采用最多的方法之一-Hierarchical cluster analysis, also known as system clustering or hierarchical clustering method, is one of the most used methods in practical work.
kde2d
- 二维高斯核函数重构 重构方法不依赖于参数化模型-2D Gaussian Kernel Reconstruction fast and accurate state-of-the-art bivariate kernel density estimator with diagonal bandwidth matrix. The kernel is assumed to be Gaussian. The two bandwidth parameter
ThemeCrawler
- 现在常见的搜索策略主要分为两种：一种是基于网页链接结构的搜索策略，另一种是基于内容评价的搜索策略。第一种是通过网页之间的链接关系来确定网页的重要性，从而决定链接访问的顺序。此方法虽然考虑了网页链接结构和网页之间的链接关系，但忽略了网页内容与主题的相关度，容易出现网页搜索“主题漂移”。第二种主要考虑网页内容，好处就是思路清晰且计算简单。但这种方法忽略了网页的链接关系，故在预测链接网页价值方面存在不足。考虑到这些问题，提出将布谷鸟搜索算法应用到主题爬虫中。-Now the common search
NJU-SSDR
- 半监督判别分析（SSDR），是南京大学数据挖掘研究所提出的一种新的半监督降维算法，对于数据挖掘和类别样本的获取有着十分重要的借鉴价值。-A semi-supervised discriminant analysis (SSDR), is one of the types of data mining research institute of nanjing university puts forward new a semi-supervised dimensionality reductio