搜索资源列表
FCM
- 核聚类算法：聚类是将一组给定的未知类标号的样本分成内在的多个类别，使得同一类中 的样本具有较高的相似度，而不同类中的样本差别大。侧重于软聚类（模糊C-均值——FCM），但其描述手段同样适合于硬聚 类（HCM）等同类问题。-Clustering algorithm: cluster is a group of unknown samples given class label into internal multiple categories, so that the same class
KNNDemo
- KNN算法Java语言实现，控制台运行界面。分类训练样本集和测试样本都有。-Java KNN language implementation, the console running interface. Classified training samples and test samples are.
Matlab
- 1.计算两类样本的隶属度；2.使用quadprog函数求解svm的拉格朗日乘子；3.主成份分析-1.caculate the membership of 2 samples；2.use quadprog function to get the lagrangian multiplier；3.principle component analasys
clustering
- samples about clustering in matlab : K-means algorithm K-medoids algorithm DBSCAN algorithm
NLPLibSVM
- libsvm分词训练集的java版本。包括libsvm.jar以及训练集样本-Libsvm version of the Java word segmentation training set. Including libsvm.jar and training set samples
JITPLS
- 自己编写的Jist-in-time PLS,利用与待估计样本最相似的若干历史样本，建立PLS回归模型，改善模型泛化能力，包含数据，直接运行，亲测可用。-I have written Jist-in-time PLS, utilization and estimated to be most similar to sample a number of historical samples, PLS regression model to establish and improve the mode
LocalOutlierFactor
- Local Outlier Factor algorithm for detection of anomaly samples.
k_nn
- kNN的思想:计算待分类的数据点与训练集所有样本点，取距离最近的k个样本；统计这k个样本的类别数量；根据多数表决方案，取数量最多的那一类作为待测样本的类别。距离度量可采用Euclidean distance，Manhattan distance和cosine。-kNN The idea is simple: the training set and calculated data points to be classified all sample points taken the neare
datamining
- 这是一个数据挖掘的算法模型，可以实现多维度、多数据、多分类的数据分析。包含对样本和数据的预处理算法，LM神经网络算法和DT决策树算法，并对两种模型进行评价的算法。-This is a data mining algorithm model, you can achieve multi-dimensional, multi-data, multi-class data analysis. Including the preprocessing algorithm for samples and d
方差分析
- 方差分析又称“变异数分析”，是R.A.Fisher发明的，用于两个及两个以上样本均数差别的显著性检验(ANOVA, also called variance analysis, was invented by R.A.Fisher, which was used to test the significance of the mean difference between two and more than two samples)
主成分和因子分析
- 主成分分析是多元统计分析中用来分析数据的一种方法，它是用一种较少数量的特征对样本进行描述以达到降低特征空间维数的方法(Principal component analysis is a method of data used in multivariate statistical analysis, it is describing the samples with characteristics of a small number of methods to reduce the dimens
knn
- 模式识别中的k近邻算法，经过测试，运行结果很好。 最小距离分类器 : 它将各类训练样本划分成若干子类，并在 每个子类中确定代表点 。测试样本的类别则以其与这些代表点距离最近作决策。该方法的缺点是所选择的代表点并不一定能很好地代表各类，其后果将使错误率增加。(The k nearest neighbor algorithm in pattern recognition has been tested and the result is very good. Minimum distance c
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序，包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)