bp neural network divided into two categories. First, there will be two types of data in savedata.m are labeled 1 and 2, and then load the data in nncw.m in the training, the last load in the test in a new test data.

BP神经网络分2类
...............\c1600w1600.mat
...............\cashmere1263.xlsx
...............\cashmere1600.xlsx
...............\cashmere2.mat
...............\checkNNGradients.m
...............\computeNumericalGradient.m
...............\debugInitializeWeights.m
...............\displayData.m
...............\fmincg.m
...............\lib
...............\...\jsonlab
...............\...\.......\AUTHORS.txt
...............\...\.......\ChangeLog.txt
...............\...\.......\jsonopt.m
...............\...\.......\LICENSE_BSD.txt
...............\...\.......\loadjson.m
...............\...\.......\loadubjson.m
...............\...\.......\mergestruct.m
...............\...\.......\README.txt
...............\...\.......\savejson.m
...............\...\.......\saveubjson.m
...............\...\.......\varargin2struct.m
...............\...\makeValidFieldName.m
...............\...\submitWithConfiguration.m
...............\New Folder
...............\..........\c127w64.mat
...............\..........\C1W2.xlsx
...............\..........\Cashmere.xlsx
...............\..........\Theta_one.mat
...............\..........\WOOL.xlsx
...............\..........\WOOL2.mat
...............\..........\WOOL2.xlsx
...............\nnCostFunction.m
...............\nnCW.m
...............\predict.m
...............\randInitializeWeights.m
...............\savedatayuan.m
...............\sigmoid.m
...............\sigmoidGradient.m
...............\submit.m
...............\test.m
...............\Theta_One.mat
...............\wool1600.xlsx
...............\wool2.mat
...............\wool520.xlsx

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