Python：K模式解釋

Question

我正在使用kmodes python庫。有人可以解釋參數的含義嗎？

鏈接： https://github.com/nicodv/kmodes#huang97

km = kmodes.KModes(n_clusters=4, init='Huang', n_init=5, verbose=1) 

我知道n_clusters是羣集組的數據進入的數量，但什麼其他參數？

Answer 1

從source code：

Parameters 
    ----------- 
    n_clusters : int, optional, default: 8 
     The number of clusters to form as well as the number of 
     centroids to generate. 
    max_iter : int, default: 300 
     Maximum number of iterations of the k-modes algorithm for a 
     single run. 
    cat_dissim : func, default: matching_dissim 
     Dissimilarity function used by the algorithm for categorical variables. 
     Defaults to the matching dissimilarity function. 
    init : {'Huang', 'Cao', 'random' or an ndarray}, default: 'Cao' 
     Method for initialization: 
     'Huang': Method in Huang [1997, 1998] 
     'Cao': Method in Cao et al. [2009] 
     'random': choose 'n_clusters' observations (rows) at random from 
     data for the initial centroids. 
     If an ndarray is passed, it should be of shape (n_clusters, n_features) 
     and gives the initial centroids. 
    n_init : int, default: 10 
     Number of time the k-modes algorithm will be run with different 
     centroid seeds. The final results will be the best output of 
     n_init consecutive runs in terms of cost. 
    verbose : int, optional 
     Verbosity mode. 

所以init只是用於初始化的方法中，而n_init是時代的算法將要運行的次數，以及那些獨立運行所選擇的最好的輸出。

verbose只是規定有多少輸出傳遞給標準輸出（即告訴你該算法在什麼階段等）。