基于模型聚類算法的matlab實現(xiàn)
This does the entire MB CLUSTERING given a set of data.
It only does the 4 basic models, unequal-unknown priors. It
returns the BESTMODEL based on the highest BIC.
Form1.cs是應(yīng)用聚類算法DBSCAN (Density-Based Spatical CLUSTERING of Application with Noise)的示例，可以通過兩個參數(shù)EPS和MinPts調(diào)節(jié)聚類。DBSCAN.cs是全部算法的實現(xiàn)文件，聚類算法的進一步信息請參考“數(shù)據(jù)挖掘”或者相關(guān)書籍。聚類示例數(shù)據(jù)來自于sxdb.mdb，一個Access數(shù)據(jù)庫。
FCMDEMO displays a GUI window to let you try out various parameters
in fuzzy c-means CLUSTERING for 2-D data. You can choose the data set
and CLUSTERING number from the GUI buttons at right, and then click
"Start" to start the fuzzy CLUSTERING process.
