Description: Handwritten recognition based on BP network. The compressed file contains the MNIST data set, runs the BPNetwork.py file directly in the pycharm, outputs the test set, identifies the results, and tests the accuracy.
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File list (Check if you may need any files):
.idea
.idea\.name
.idea\BPNetwork.iml
.idea\encodings.xml
.idea\misc.xml
.idea\modules.xml
.idea\scopes
.idea\scopes\scope_settings.xml
.idea\vcs.xml
.idea\workspace.xml
__pycache__
__pycache__\get_test_num.cpython-35.pyc
__pycache__\input_data.cpython-35.pyc
__pycache__\mnist_demo.cpython-35.pyc
BPNetwork.py
get_test_num.py
mnist_test.mat
mnist_test_labels.mat
mnist_train.mat
mnist_train_labels.mat
MyNetWork
readme.txt
test_num
test_num\107.png
test_num\157.png
test_num\185.png
test_num\186.png
test_num\187.png
test_num\197.png
test_num\229.png
test_num\49.png
test_num\84.png
test_num\90.png
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