classificationModel       package:gene2pathway       R Documentation

_H_i_e_r_a_r_c_h_i_c_a_l _C_l_a_s_s_i_f_i_c_a_t_i_o_n _M_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     This file contains the hierarchical classification model to
     predict KEGG pathway branches for genes. The model uses a pruned
     KEGG hierarchy, where metabolic pathways are not distinguished
     further, and the KEGG hierarchy for "cellular processes" and
     "genetic information processing" is pruned at the 2nd level. By
     default the model uses bagging to improve prediction accuracy.
     Important: There exists one separate model file for each organism.

_F_o_r_m_a_t:

     List of class "model", where each model has the following entries:

     _W learned decision hyperplane normal vector

     _C dictionary of label vectors, which can be predicted individually
          or which can be used to predict combinations of them

     _d_e_t_e_c_t_o_r_s SVM models trained to separate one specific pathway
          branch from the rest of the hierarchy

     _u_s_e_d__d_o_m_a_i_n_s InterPro domains used by the classifier to separate
          the specific branch from the rest of the hierarchy

     _a_l_l_d_o_m_a_i_n_s all InterPro domains used to build feature vectors

     _a_l_l_p_a_t_h_w_a_y_s hierarchy branches, which can be predicted

     _t_r_e_e_s_i_z_e_s relative size of hierarchy below the corresponding
          branch

     _k_e_g_g__h_i_e_r_a_r_c_h_y a nested list with information (parent branches,
          pathway names, pathway IDs, hierarchy level) on all higher
          hierarchy branches for each pathway

_A_u_t_h_o_r(_s):

     Holger Froehlich

_S_e_e _A_l_s_o:

     'classificationModelSignalTrans'

