搜索资源列表
gmeans
- gmeans-- Clustering with first variation and splitting 文本聚类算法Gmeans ,使用了3种相似度函数,cosine,euclidean ,KL.文本数据使用的是稀疏矩阵形式. -gmeans clustering with first variation and splitting Gmeans,a text clustering algorithm, uses 3 functions,cosine,euclidean and
POSTagger
- （1）从已经标注好词性的语料中统计得到词性标记的二元转移矩阵，以及每个词以确定的词性标记出现的次数等数据（训练阶段） （2）利用动态规划算法快速选取词性标记路径，得到词性标记结果 （3）可以选择不同的词性标记集 -(1) from the good part-of-speech tagging has been the Corpus statistics to be part of speech marking the transfer of binary matrix, a
discriminable_matirx_builder
- 实现了粗糙集理论的可辨识矩阵的生成，输入为一个文本文件的数据方阵，以数据之间用Tab分开，用回车键分行，用Skowron用可辨识矩阵的方法实现对不分明类的生成。压缩包里面还有一个测试数据。-realization of the rough set theory of identification matrix generation, import text files to a data matrix. Data used to Tab between the separate branches
IntroMatlab_codepls
- PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis
LS-TLS
- LS和TLS算法原理及其Matlab仿真,未知的参数向量 常可以建模成矩阵方程 ，A和b分别是与观测数据有关的系数矩阵的向量。通过使误差的平方和最小来确定参数估计向量 。所求得的估计成为最小二乘估计 -LS and TLS Algorithm and its Matlab simulation, the unknown constant parameter vector into a matrix equation can be modeled, A and b are coefficien
selfAffinity
- AP是在数据点的相似度矩阵的基础上进行聚类.对于规模很大的数据集,AP算法是一种快速、有效的聚类方法,这是其他传统的聚类算法所不能及的,-A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP
bp_v1_2
- -----引入动量的算法 建立一个3层（含输入层）的BP神经网络，并对其进行训练 输入层不进行数据处理，隐含层激活函数为sigmod函数，输出层为线性函数 输入输出数据归一化到[-1,1]，数据在矩阵中按行向量表示 即x=[x11,x12 x21,x22 ... xp1,xp2] y=[y1 y2 ... yp] p为样本数 -The introduction of the algorithm ----- momentum to build a three-layer (
PCA_for_3_component_compound
- 该程序旨在模拟处理分析多种化学物质混合物的吸收光谱数据，提取出各个化学成分的峰值所在。该程序采用svd方法对光谱数据的协方差矩阵进行PCA分析，并且取得令人满意的效果。-The program designed to simulate the processing and analysis of multiple chemical mixtures of the absorption spectra of the data, extracting the chemical composition
Fuzzyclusteringcode
- 通过收集数据来建立模糊聚类相似矩阵来对数据进行统计很方便-By collecting data to establish fuzzy similar matrix to cluster the data statistics is easy
fcbo
- fcbo - 计算形式概念和最大频繁项集。这 程序计算对象属性集（形式背景）的所有形式概念的内涵，即算法计算一个布尔矩阵。-fcbo- computes formal concepts and maximal frequent itemsets. This program computes intents of all formal concepts in an object-attribute data set (a formal context), i.e. the algo
nmf(train)
- 用于入侵检测系统开发的非负矩阵分解算法，用于对KDD99数据进行样本训练。-Intrusion detection system for the development of non-negative matrix factorization algorithm, the data sample used for KDD99 training.
iris
- 数据挖掘经典数据，鸢尾花分类，txt形式矩阵，直接使用非常方便。-Classical data mining data, iris classification, the form of TXT matrix directly, very convenient to use.
PCA
- 实用的主分量分析程序。程序中mixedsig为 n*T 阶混合数据矩阵，n为信号个数，T为采样点数, y为 m*T 阶主分量矩阵。-The practical primary component analysis program. Program mixedsig n* T Order Mixed data matrix, n is the number of signals, T is the sampling points, y is M* T stage primary component
kmeans1
- K-means算法，算法步骤如下： Step1.利用式(2)计算距离矩阵D=()，其中=dist[i, j] ()； Step2.扫描坐标距离矩阵D，寻找距离的最大值和最小值，用式(3)计算limit； Step3.扫描坐标距离矩阵D，寻找矩阵中距离最小的2个数据a，b，将数据a，b加入集合，={a,b}，同时将数据a，b从U中删除，更新距离矩阵D； Step4.利用 (4)式在U中寻找距离集合最近的数据样本t，如果小于limit，则将t加入集合，同时将t从集合U中删除，更新
AP-Cluster
- AP聚类算法的C++代码实现，其中数据是文本读入iris数据，P值选取欧式矩阵最小值。显示结果为聚类后结果-AP clustering algorithm C++ code, in which data is read into the text iris data, P values selected European matrix minimum. Showing results clustering results after
Clustering
- In multivariate statistics and the clustering of data, spectral clustering[1] techniques make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions. The simila
smo.tar
- This an implementation of SMO type classifier[1]. The input file is "i_x.mat" which is the matrix form of ionoshpere data obtained from https://archive.ics.uci.edu/ml/datasets.html [1] http://www.csie.ntu.edu.tw/~cjlin/papers/quadworkset.pdf-Thi
NB
- 朴素贝叶斯分类器，Data为总数据矩阵,Train_Dat为训练样本,Test_Dat为测试样本，用来实现对测试样本进行分类~可以从UCI下载数据调用使用~-Naive Bayes classifier, Data for the total data matrix, Train_Dat of training samples, Test_Dat test sample, the test samples were used to achieve the classification of ~
svdRec
- 机器学习算法，利用SVD简化数据，SVD矩阵分解，推荐引擎，提高性能-Machine learning algorithm, using SVD simplify data, SVD matrix decomposition, recommendation engine, improved performance
PCA程序
- 实现主成分分析 % Usage: % [eigvector, eigvalue] = PCA(data, options) % [eigvector, eigvalue] = PCA(data) % % Input: % data - Data matrix. Each row vector of fea is a data point. % % options.ReducedDim