pamr.plotcvprob             package:pamr             R Documentation

_A _f_u_n_c_t_i_o_n _t_o _p_l_o_t _t_h_e _c_r_o_s_s-_v_a_l_i_d_a_t_e_d _s_a_m_p_l_e _p_r_o_b_a_b_i_l_i_t_i_e_s _f_r_o_m
_t_h_e _n_e_a_r_e_s_t _s_h_r_u_n_k_e_n _c_e_n_t_r_o_i_d
_c_l_a_s_s_i_f_i_e_r

_D_e_s_c_r_i_p_t_i_o_n:

     A function to plot the cross-validated sample probabilities from 
     the nearest shrunken centroid classifier

_U_s_a_g_e:

     pamr.plotcvprob(fit, data, threshold)

_A_r_g_u_m_e_n_t_s:

     fit: The result of a call to pamr.cv

    data: A list with at least two components: x- an expression genes
          in the rows, samples in the columns), and y-  a vector of the
          class labels for each sample. Same form as data object used
          by pamr.train.

threshold: Threshold value to be used

_D_e_t_a_i_l_s:

     'pamr.plotcvprob' plots the cross-validated sample probabilities 
     the from nearest shrunken centroid classifier, stratified by the
     true classses.

_V_a_l_u_e:

_A_u_t_h_o_r(_s):

     Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and
     Gilbert Chu

_R_e_f_e_r_e_n_c_e_s:

_E_x_a_m_p_l_e_s:

     set.seed(120)
     x <- matrix(rnorm(1000*20),ncol=20)
     y <- sample(c(1:4),size=20,replace=TRUE)
     mydata <- list(x=x,y=y)
     mytrain <-   pamr.train(mydata)
     mycv <-  pamr.cv(mytrain,mydata)
     pamr.plotcvprob(mycv,mydata,threshold=1.6)

