DBN-ELM-master

代码说明：

说明：  DBN-ELM应用于软测量，可以预测精度，并且可以和其它软测量模型进行对比。(Application of DBN-ELM in Soft Sensing,it can predict the accuracy and compare with other soft sensor models.)

文件列表：

DBN-ELM-master, 0 , 2018-04-30
DBN-ELM-master\README.md, 315 , 2018-04-30
DBN-ELM-master\matlab, 0 , 2018-04-30
DBN-ELM-master\matlab\README.md, 100 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin, 0 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\CG_CLASSIFY.m, 1852 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\CG_CLASSIFY_INIT.m, 1158 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\DBN_ELM.m, 4141 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\DBN_ELM_CL.m, 7210 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\DBN_ELM_one_layer.m, 2961 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\DBN_ELM_two_layer.m, 3543 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\ELM.m, 4241 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\README.md, 1 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\backpropclassify.m, 7313 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\dbnelmclvoit.m, 1559 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\elmplot.m, 5029 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\makedata.m, 3099 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\minimize.m, 9335 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\mnistclassify.m, 2301 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\rbm.m, 4521 , 2018-04-30
DBN-ELM-master\matlab\Skin_NonSkin\rbmhidlinear.m, 4415 , 2018-04-30
DBN-ELM-master\matlab\mnist, 0 , 2018-04-30
DBN-ELM-master\matlab\mnist\CG_CLASSIFY.m, 1853 , 2018-04-30
DBN-ELM-master\matlab\mnist\CG_CLASSIFY_INIT.m, 1136 , 2018-04-30
DBN-ELM-master\matlab\mnist\DBN_ELM.m, 4766 , 2018-04-30
DBN-ELM-master\matlab\mnist\DBN_ELM_CL.m, 7520 , 2018-04-30
DBN-ELM-master\matlab\mnist\DBN_ELM_one_layer.m, 3416 , 2018-04-30
DBN-ELM-master\matlab\mnist\DBN_ELM_two_layer.m, 4219 , 2018-04-30
DBN-ELM-master\matlab\mnist\ELM.m, 4828 , 2018-04-30
DBN-ELM-master\matlab\mnist\ML_ELM.m, 3355 , 2018-04-30
DBN-ELM-master\matlab\mnist\ML_ELM_two_layer.m, 3362 , 2018-04-30
DBN-ELM-master\matlab\mnist\README.md, 47 , 2018-04-30
DBN-ELM-master\matlab\mnist\backprop.m, 6216 , 2018-04-30
DBN-ELM-master\matlab\mnist\backpropclassify.m, 7167 , 2018-04-30
DBN-ELM-master\matlab\mnist\converter.m, 3739 , 2018-04-30
DBN-ELM-master\matlab\mnist\dbnelmclvoit.m, 1490 , 2018-04-30
DBN-ELM-master\matlab\mnist\dbnelmplot.m, 5795 , 2018-04-30
DBN-ELM-master\matlab\mnist\elmplot.m, 5125 , 2018-04-30
DBN-ELM-master\matlab\mnist\makebatches.m, 6368 , 2018-04-30
DBN-ELM-master\matlab\mnist\minimize.m, 9335 , 2018-04-30
DBN-ELM-master\matlab\mnist\mlelmplot.m, 4830 , 2018-04-30
DBN-ELM-master\matlab\mnist\mnistclassify.m, 2109 , 2018-04-30
DBN-ELM-master\matlab\mnist\mnistdeepauto.m, 2896 , 2018-04-30
DBN-ELM-master\matlab\mnist\mnisthp2classify.mat, 7676885 , 2018-04-30
DBN-ELM-master\matlab\mnist\plottest.m, 764 , 2018-04-30
DBN-ELM-master\matlab\mnist\rbm.m, 4521 , 2018-04-30
DBN-ELM-master\matlab\mnist\rbmhidlinear.m, 4415 , 2018-04-30
DBN-ELM-master\python, 0 , 2018-04-30
DBN-ELM-master\python\README.md, 191 , 2018-04-30
DBN-ELM-master\python\myelm.py, 26134 , 2018-04-30
DBN-ELM-master\python\myelmdbn.py, 22151 , 2018-04-30