znorm                 package:dprep                 R Documentation

_Z-_s_c_o_r_e _n_o_r_m_a_l_i_z_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This is a function to apply z-Score normalization to a matrix or
     dataframe.

_U_s_a_g_e:

     znorm(data)

_A_r_g_u_m_e_n_t_s:

    data: the dataset to be normalized, including classes

_D_e_t_a_i_l_s:

     By using this type of normalization, the mean of th transformed
     set of data points is reduced to zero by subtracting the mean of
     each attribute from the values of the attributes and dividing the
     result by the standard deviation of the attribute. Uses the
     function scale found in the base library.

     Removes classes before normalization, and returns normalized data
     set complete with classes rejoined.

_V_a_l_u_e:

   zdata: the normalized data set

_A_u_t_h_o_r(_s):

     Caroline Rodriguez and Edgar Acuna

_R_e_f_e_r_e_n_c_e_s:

     Hann, J., Kamber, M. (2000). Data Mining: Concepts and Techniques.
      Morgan Kaufman Publishers.

_E_x_a_m_p_l_e_s:

     ##---- Z-norm normalization ----
     data(diabetes)
     diab.znorm=znorm(diabetes)
     op=par(mfrow=c(2,1))
     plot(diabetes[,1])
     plot(diab.znorm[,1])
     par(op)

