MLIclust            package:MLInterfaces            R Documentation

_A_n _i_n_t_e_r_f_a_c_e _t_o _v_a_r_i_o_u_s _u_n_s_u_p_e_r_v_i_s_e_d _m_a_c_h_i_n_e _l_e_a_r_n_i_n_g _m_e_t_h_o_d_s _f_o_r _E_x_p_r_e_s_s_i_o_n_S_e_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     This document describes a family of wrappers to R functions that
     perform clustering of multivariate datasets. For example, the
     'kmeansB' function is a wrapper for a call to 'kmeans' for objects
     of class 'ExpressionSet'. The interfaces of 'MLInterfaces' provide
     a common calling sequence and common return value for machine
     learning code.

_U_s_a_g_e:

     kmeansB(exprObj, k , iter.max, metric = "euclidean") 

_A_r_g_u_m_e_n_t_s:

 exprObj: An instance of the 'exprset' class. 

       k: The number of clusters

iter.max: The maximum number of iterations to perform.

  metric: See 'knn' for a complete description. 

_D_e_t_a_i_l_s:

     See 'kmeans' for a complete description, and for other functions
     named [f]B, see the documentation on 'f'.

_V_a_l_u_e:

     An object of class 'clustOutput-class'.

_A_u_t_h_o_r(_s):

     Jess Mar, VJ Carey <stvjc@channing.harvard.edu>

_S_e_e _A_l_s_o:

     'ldaB'

_E_x_a_m_p_l_e_s:

     ##get these from the source files
     library(golubEsets)
     data(Golub_Merge)
     smallG <- Golub_Merge[1:60,]
     set.seed(1234) # needed for nnet initialization
     kmeansB( smallG, k=4 )
     agnesB( smallG, k=5, height=0, FALSE )
     dianaB( smallG, k=5, height=0, FALSE )
     pamB( smallG, k=5, height=0, FALSE )
     bclustB( smallG, k=5, height=0 )
     cmeansB( smallG, k=5, height=0 )
     cshellB( smallG, k=5, height=0 , iter.max=1)
     #lcaB( BsmG, k=3 )
     hclustB( smallG, k=4 )
     hclustB( smallG, height=40000 )

