mmnorm                 package:dprep                 R Documentation

_M_i_n-_m_a_x _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 min-max normalization to a matrix or
     dataframe.

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

     mmnorm(data,minval=0,maxval=1)

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

    data: the dataset to be normalized, including classes

  minval: 

  maxval: 

     {the maximum value of the transformed range}

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

     Min-max normalization subtracts the minimum value of an attribute
     from each value of the attribute and then divides the difference
     by the range of the attribute. These new values are multiplied by
     the new range of the attribute and finally added to the new
     minimum value of the attribute. These operations transform the
     data into a new range, generally [0,1].

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

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

  zdata3: the original dataset normalized by min-max normalization.

_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:

     #---- Min-Max Normalization----
     data(ionosphere)
     ionos.minmax=mmnorm(ionosphere)
     op=par(mfrow=c(2,1))
     plot(ionosphere[,1])
     plot(ionos.minmax[,1])
     par(op)

