BIC确定GMM聚类簇数

这是一本经典数值算法书,包含多种算法的理论,为编程者具有一定参考意义()

求解矩阵的最大最小特征值及对应的特征向量,以及计算条件数()

用Apriori算法挖掘出入侵检测数据集KDD99的数据关联性，从而检测出未知的攻击(Apriori algorithm is used to extract the data association of the intrusion detection data set KDD99, and the unknown attack is detected)

说明：  将数据集转换为拉普拉斯矩阵，然后利用基于图论的谱聚类进行聚类。拉普拉斯矩阵采用高斯核函数，全连接方法计算。谱聚类擅长处理高维数据或非凸数据集。(The data set is transformed into Laplacian matrix, and then clustered by spectral clustering based on graph theory. The Laplacian matrix is calculated by using the Gauss kernel function and the full connection method. Spectral clustering is good at dealing with high-dimensional or non-convex data sets.)

数据挖掘经典算法，频繁项集挖掘经典算法，FPGROWTH算法，源码中有详细说明

一种特征提取方法：结合主元分析(PCA)和核主元分析（KPCA）的前馈神经网络（FNN）(A feature extraction method: the feedforward neural network (FNN) combined with principal component analysis (PCA) and kernel principal component analysis (KPCA))

机器学习与R语言（machine_learning）源代码下载，内含R语言实现机器学习算法和应用案例(Machine learning and R language (machine_learning) source code download, containing R language to implement machine learning algorithms and application cases)

通过包围盒法和K-D树法实现电云数据的邻域收索，邻域值可以自动设置(Point cloud data by bounding boxes and K-D tree search method income neighborhood, neighborhood values can be automatically set)

用C++实现各种排序算法：如冒泡排序,选择排序,插入排序,希尔排序,快速排序,归并排序,基数排序和堆排序,并带有源代码说明()

资源描述实现基本的pagerank算法，可实现传递阻尼参数和迭代次数。源文件从文件中读取