clc;clear;close?all
disp（‘原始數據，不同預處理方法進行處理的RMSECVRMSEP訓練集及預測集的R‘）
load?UV
cal????=?calset（:1:600）;
caltar?=?calsettar;
for?columm??=?1:4;
????dataname???=?ynames{columm};
????disp（dataname）;??????
???%----------------------------因子數的確定--------------------------------
???switch?columm
????case?1
?????????maxrank?=?8;
????????
????case?2
?????????maxrank?=?6;
?????????
????case?3
?????????maxrank?=?7;
????????
????case?4
?????????maxrank?=?6;????
????end?
????[mn]?????????????????????=?size（cal）;
????%-----------------KS對數據劃分，訓練集2/3，預測集1/3---------------------
????[modeltest]????????????????????=?kenstone（calfloor（2/3*m））;
????x_train?????????????????????????=?cal（model:）;
????x_pred??????????????????????????=?cal（test:）;
????y_train?????????????????????????=?caltar（modelcolumm）;
????y_pred??????????????????????????=?caltar（testcolumm）;
????[m_trainn_train]???????????????=?size（x_train）;
????%-------------------------------PLS------------------------------------
????disp（‘偏最小二乘-PLS‘）
????b???????????????????????????????=?simpls（x_trainy_trainmaxrank）;
????c???????????????????????????????=?x_pred*b（:maxrank）;
????[c_trainvalpresses]????????????=?loocv（x_trainy_trainmaxrank）;
????disp（‘RMSECVRMSEP訓練集及預測集的R‘）;
????rmsecv_PLS??????????????????????=?sqrt（valpresses./m_train）;
????rmsep_PLS???????????????????????=?rms（c-y_pred）;
????r_train?????????????????????????=?corrcoef（c_trainy_train）;
????r_train?????????????????????????=?r_train（12）;
????r_PLS???????????????????????????=?corrcoef（cy_pred）;
????r_PLS???????????????????????????=?r_PLS（12）;
????disp（[rmsecv_PLSrmsep_PLSr_trainr_PLS]）;
????disp（‘回收率最大最小值‘）;
????recovery_PLS????????????????????=?100*c./y_pred;
????max_recovery_PLS（columm）????????=?max（recovery_PLS）;
????min_recovery_PLS（columm）????????=?min（recovery_PLS）;
????disp（[max_recovery_PLS（columm）min_recovery_PLS（columm）]）;
????clear?b?c?c_train?valpresses?r_train?
????%-----------------------------