classifyNewSamples-methods      package:Rmagpie      R Documentation

_c_l_a_s_s_i_f_y_N_e_w_S_a_m_p_l_e_s _M_e_t_h_o_d _t_o _c_l_a_s_s_i_f_y _n_e_w _s_a_m_p_l_e_s _f_o_r _a _g_i_v_e_n _a_s_s_e_s_s_m_e_n_t

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

     This method classify one or several new samples provided in the
     file 'newSamplesFile' using the final classifier build by
     'findFinalClassifier'.

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

  object: 'object of class assessment'. Object assessment of interest

newSamplesFile: 'character'. URL of the file containing the gene
          expressions of the samples to be classified. The first line
          of the file must corresponds to the sample names and the
          first column to the names of the genes.

optionValue: 'numeric'. Size of subset (for RFE-SVM) or threshold (for
          NSC) to be considered, the option value  must be available in
          the slot 'featureSelectionOptions' of the assessment. If not,
          the smallest value bigger than 'optionValue' is selected. If
          this argument is missing the best option value according to
          one-layer cross-validation is used.

_M_e_t_h_o_d_s:



     _o_b_j_e_c_t = "_a_s_s_e_s_s_m_e_n_t" This method is only applicable on objects of
          class assessment.

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

     data('vV70genesDataset')

     expeOfInterest <- new("assessment", dataset=vV70genes,
                                        noFolds1stLayer=10,
                                        noFolds2ndLayer=9,
                                        classifierName="svm",
                                        typeFoldCreation="original",
                                        svmKernel="linear",
                                        noOfRepeat=2,
                                        featureSelectionOptions=new("geneSubsets", optionValues=c(1,2,4,8,16,32,64,70)))

     # Build the final classifier
     expeOfInterest <- findFinalClassifier(expeOfInterest)

     ## Not run: 
     classifyNewSamples(expeOfInterest, "pathToFile/testSamples_geneExpr.txt", 4)
     ## End(Not run)
     expeOfInterest <- runOneLayerExtCV(expeOfInterest)
     ## Not run: 
     classifyNewSamples(expeOfInterest, "pathToFile/testSamples_geneExpr.txt")
     ## End(Not run)

