搜索资源列表
kmeans
- k均值聚类方法。 在给定一个有n个对象的数据集，划分聚类技术将构造数据进行k个划分，每一个划分代表一个簇，k小于等于n。-k-means clustering method. Given a set of n objects data, dividing the data clustering techniques to construct k partitions, each partition represents a cluster, k less than or equal n.
a-decentralized-positioning-scheme
- 根据资料中的论文，部分编写了代码验证了该方案，实现了该定位方法的仿真。-According to the data in the paper, part of the proposed method is validated through the code, and realize the simulation of the positioning method.
fin_cpp
- fin-cpp算法，是一种快速频繁项挖掘算法，比fpgrownth还要快。SCI已发表认证-fin-cpp, a fast frequent itemsets method
LOW-density-seperation
- 使用LDS(low density seperation)method 寻找最优分离面，然后对数据进行分类-Use LDS (low density seperation) method to find the optimal separation surface, and then classify the data
stft
- 利用时频分析的方法分析一段语音信号的时频特征，并进行降采样等处理，可直接运行-When the time-frequency analysis method to analyze the frequency of use of a voice signal characteristics, and down-sampling and other treatment, can be directly run
bipls
- bipls变量选择方法的matlab代码，包括所有有关代码- bipls variable selection method matlab code, including all relevant codes
CliqueB
- 基于派系方法的社团结构划分算法，自己实现的，C++代码源程序。-A method of community structure based clique.
k-means-Java
- 用JAVA实现k-means算法，其中聚类方法使用余弦相似度,带运行界面。完美运行。-Using JAVA k-means algorithm, clustering method using the cosine similarity
era
- 基于时域的模态参数识别算法，特征系统实现法。-Modal parameter identification algorithm based on time domain, the characteristics of the system implementation method.
VAR
- 时域模态分析方法中的多元自回归模型，用于识别结构的模态参数。-Multivariate autoregressive model of time domain modal analysis method, is used to identify structural modal parameters.
Lmethod
- L-method in R statistical language. Implementation of the L-method algorithm for finding the best number of clusters in hierarchical clustering. Algorithm is described here: Salvador, S. and Chan, P., 2004. Determining the number of clusters/seg
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
Multistep-Wind-Speed-Forecasting-Based-on-Wavelet
- Considering the randomness and volatility of wind, a method based on B-spline neural network optimized by particle swarm optimization is proposed to predict the short-term wind speed
zishiyingguolvfa
- 自适应过滤法是根据一组给定的权数对时间数列的历史观察值进行加权平均计算一个预测值，然后根据预测误差调整权数以减少误差，这样反复进行直至找出一组“最佳”权数，使误差减少到最低限度，再利用最佳权数进行加权平均预测。-Adaptive filtering method is based on the number of a given set of rights to compute a weighted average of the predicted value of historical tim
xyle
- 拉普拉斯降维方法，是非线性数据降维方法，通过构建相似关系图来重构数据局部流形结构特征。-Laplace dimension reduction method is non-linear data dimensionality reduction method, by constructing a graph similar to reconstruct the structure of local manifoldof the data.
mani
- 此代码是关于流形学习，数据降维，代码中含有的主要方法是PCA，KPCA，MDS，KMDS，Laplacian等等，且代码作了可视化处理，界面效果完美-This code is on the manifold learning, data dimensionality reduction, the main method code is contained in PCA, KPCA, MDS, KMDS, Laplacian, etc., and the code visualization ma
project-1-skeleton
- 本压缩包内有决策树，knn，linear的方法（包括10-fold） 替换data可以直接使用。-You can find decision tree, inn and linear method in my zip, include 10-fold. The data.py can replaced by yourself
log
- 提出基于拉普拉斯高斯（Laplacian of Gaussian，LoG）算子边缘检测的全局二值化方法对其进行处理，该方法通过提取图像边缘部份的像素灰度获得图像二值化的阈值。处理结果表明，与传统的几种方法相比，该方法能够快速选取良好的二值化阈值，较好地区分目标和背景，在相当大模板宽度内图像二值化的结果都令人满意。-Is put forward based on the Laplacian of Gaussian (LoG) Laplacian of Gaussian, operator edge
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.
Batch-Gradient-Descent
- 分别使用了批梯度下降法和牛顿法进行线性回归的测试。-Respectively the batch gradient descent and Newton s method of linear regression tests.