宽度学习 Broad Learning System MATLAB 代码1:MNIST实践
澳门大学陈俊龙 | 宽度学习系统:一种不需要深度结构的高效增量学习系统
原文 Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture
IEEE Transactions on Neural Networks and Learning Systems, Vol. 29, Issue 1, 2018
代码片段和文件信息
属性 大小 日期 时间 名称
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文件 9687 2017-11-27 22:51 Demo_Broadlearning_MNISTBLS_demo_MNIST.m
文件 9752 2017-11-27 22:52 Demo_Broadlearning_MNISTBLS_demo_MNIST_for_lower_memory.m
文件 3028 2017-07-16 19:35 Demo_Broadlearning_MNISTls_train.m
文件 7776 2017-07-19 23:17 Demo_Broadlearning_MNISTls_train_bp.m
文件 5834 2017-07-16 19:43 Demo_Broadlearning_MNISTls_train_enhance.m
文件 6745 2017-07-16 20:28 Demo_Broadlearning_MNISTls_train_enhancefeature.m
文件 5639 2017-07-16 20:31 Demo_Broadlearning_MNISTls_train_input.m
文件 6398 2017-07-16 20:32 Demo_Broadlearning_MNISTls_train_inputenhance.m
文件 14735220 2017-07-11 20:58 Demo_Broadlearning_MNISTmnist.mat
文件 438 2017-07-19 23:02 Demo_Broadlearning_MNISTpre_zca.m
文件 72 2017-07-11 20:58 Demo_Broadlearning_MNIST
esult.m
文件 495 2017-07-11 20:58 Demo_Broadlearning_MNISTsparse_bls.m
目录 0 2017-11-27 22:52 Demo_Broadlearning_MNIST
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%%%%%%%%%%%%%%%%%%%%%%%%This is the demo for the bls models including the
%%%%%%%%%%%%%%%%%%%%%%%%proposed incremental learning algorithms.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%load the dataset MNIST dataset%%%%%%%%%%%%%%%%%%%%
clear;
warning off all;
format compact;
load mnist;
%%%%%%%%%%%%%%%the samples from the data are normalized and the lable data
%%%%%%%%%%%%%%%train_y and test_y are reset as N*C matrices%%%%%%%%%%%%%%
train_x = double(train_x/255);
train_y = double(train_y);
% test_x = double(train_x/255);
% test_y = double(train_y);
test_x = double(test_x/255);
test_y = double(test_y);
train_y=(train_y-1)*2+1;
test_y=(test_y-1)*2+1;
assert(isfloat(train_x) ‘train_x must be a float‘);
assert(all(train_x(:)>=0) && all(train_x(:)<=1) ‘all data in train_x must be in [0:1]‘);
assert(isfloat(test_x) ‘test_x must be a float‘);
assert(all(test_x(:)>=0) && all(test_x(:)<=1) ‘all data in test_x must be in [0:1]‘);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
disp(‘Press any key to run the one shot BLS demo‘);
pause
%%%%%%%%%%%%%%%%%%%%This is the model of broad learning sytem with%%%%%%
%%%%%%%%%%%%%%%%%%%%one shot structrue%%%%%%%%%%%%%%%%%%%%%%%%
C = 2^-30; s = .8;%the l2 regularization parameter and the shrinkage scale of the enhancement nodes
N11=10;%feature nodes per window
N2=10;% number of windows of feature nodes
N33=11000;% number of enhancement nodes
epochs=10;% number of epochs
train_err=zeros(1epochs);test_err=zeros(1epochs);
train_time=zeros(1epochs);test_time=zeros(1epochs);
% rand(‘state‘67797325) % 12000 %%%%% The random seed recommended by the
% reference HELM [10].
N1=N11; N3=N33;
for j=1:epochs
[TrainingAccuracyTestingAccuracyTraining_timeTesting_time] = bls_train(train_xtrain_ytest_xtest_ysCN1N2N3);
train_err(j)=TrainingAccuracy * 100;
test_err(j)=TestingAccuracy * 100;
train_time(j)=Training_time;
test_time(j)=Testing_time;
end
save ( [‘mnist_result_oneshot_‘ num2str(N3)] ‘train_err‘ ‘test_err‘ ‘train_time‘ ‘test_time‘);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
disp(‘Press any key to run the one shot BLS demo with BP algorithm‘);
pause
%%%%%%%%%%%%%%%%%%%%This is the model of broad learning system for one%%%%%%
%%%%%%%%%%%%%%%%%%%%shot structrue with fine tuning under BP algorithm%%%%%%%%%%%%%%%%%%%%%%%%
C = 2^-30; s = .8;%the l2 regularization parameter and the shrinkage scale of the enhancement nodes
N11=10;%feature nodes per window
N2=10;% number of windows of feature nodes
N33=5000;% number of enhancement nodes
epochs=1;% number of epochs
train_err=zeros(1epochs);test_err=zeros(1epochs);
train_time=zeros(1epochs);test_time=zeros(1epochs);
% rand(‘state‘67797325) % 12000 %%%%% The random seed recommended by the
% reference HELM [10].
N1=N11; N3=N33;
for j=1:epochs
[TrainingAcc
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 9687 2017-11-27 22:51 Demo_Broadlearning_MNISTBLS_demo_MNIST.m
文件 9752 2017-11-27 22:52 Demo_Broadlearning_MNISTBLS_demo_MNIST_for_lower_memory.m
文件 3028 2017-07-16 19:35 Demo_Broadlearning_MNISTls_train.m
文件 7776 2017-07-19 23:17 Demo_Broadlearning_MNISTls_train_bp.m
文件 5834 2017-07-16 19:43 Demo_Broadlearning_MNISTls_train_enhance.m
文件 6745 2017-07-16 20:28 Demo_Broadlearning_MNISTls_train_enhancefeature.m
文件 5639 2017-07-16 20:31 Demo_Broadlearning_MNISTls_train_input.m
文件 6398 2017-07-16 20:32 Demo_Broadlearning_MNISTls_train_inputenhance.m
文件 14735220 2017-07-11 20:58 Demo_Broadlearning_MNISTmnist.mat
文件 438 2017-07-19 23:02 Demo_Broadlearning_MNISTpre_zca.m
文件 72 2017-07-11 20:58 Demo_Broadlearning_MNIST
esult.m
文件 495 2017-07-11 20:58 Demo_Broadlearning_MNISTsparse_bls.m
目录 0 2017-11-27 22:52 Demo_Broadlearning_MNIST
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