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How to use BP network tools, I believe that many inexperienced people do not know what to do, so this paper summarizes the causes of the problem and solutions, through this article I hope you can solve this problem.

BP (Back Propagation) neural network was proposed by a group of scientists headed by Rumelhart and McCelland in 1986. It is a multi-layer feedforward network trained by error back propagation algorithm. It is one of the most widely used neural network models at present. BP network can learn and store a large number of input-output pattern mapping relations without revealing the mathematical equations describing this mapping relationship in advance. Its learning rule is to use the gradient descent method to constantly adjust the weights and thresholds of the network through back propagation to minimize the sum of squared errors of the network. The topology of BP neural network model includes input layer (input), hidden layer (hidden layer) and output layer (output layer).

Neural network can be used for classification, clustering, prediction and so on. The neural network needs a certain amount of historical data. Through the training of the historical data, the network can learn the hidden knowledge in the data.

% cleanup

Clear,clc

Rng ('default')

Rng (2)

%% read in data

Xlsfile='student.xls'

[data,label] = getdata (xlsfile)

%% partition data

[traind,trainl,testd,testl] = divide (data,label)

Create network

Net=feedforwardnet (3)

Net.trainFcn='trainbfg'

%% training network

Net=train (net,traind',trainl)

%% Test

Test_out=sim (net,testd')

Test_out (test_out > = 0.5) = 1

Test_out (test_out

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