Search - K-centres

Search - K-centres - List

[Mathimatics-Numerical algorithms] kmeansNetlab DL : 0: KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The point at which a local minimum is achieved is returned as CENTRES.
Update : 2008-10-13 Size : 1.88kb Publisher : 西晃云
[AI-NN-PR] kmean DL : 0: 模式识别算法 k均值和感知器算法的具体实现实例-Pattern recognition algorithm for k-means algorithm and the perceptron realize specific examples
Update : 2025-04-04 Size : 173kb Publisher : fengyuan
[Mathimatics-Numerical algorithms] kmeansNetlab DL : 0: KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The point at which a local minimum is achieved is returned as CENTRES.
Update : 2025-04-04 Size : 2kb Publisher : 西晃云
[AI-NN-PR] k-means DL : 0: 这是K均值算法,采用c语言编写,K的取值为2,大家可以改变K的值来进行测试-This is the K-means algorithm, using c language, K value of 2, we can change the value of K for testing
Update : 2025-04-04 Size : 313kb Publisher : Gang Li
[matlab] GM_EM DL : 0: 不错的GM_EM代码。用于聚类分析等方面。- GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres
Update : 2025-04-04 Size : 3kb Publisher : 朱魏
[DataMining] zolam DL : 0: KMEANS Trains a k means cluster model CENTRES KMEANS(CENTRES,()
Update : 2025-04-04 Size : 1kb Publisher : rrogzzms
[Special Effects] 7018267 DL : 0: KMEANS Trains a k means cluster model CENTRES KMEANS(CENTRES,()
Update : 2025-04-04 Size : 1kb Publisher : Abelit