代码搜索:BackProp

找到约 426 项符合「BackProp」的源代码

代码结果 426
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java backprop.java

/* Copyright 2006, 2007 Brian Greer This file is part of the Java NN Trainer. Java NN Trainer is free software; you can redistribute it and/or modify it under the terms of the GNU General Public
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cpp backprop.cpp

/* ****************************************************************** * backprop.cpp ****************************************************************** */ #include "StdAfx.h" #include #
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h backprop.h

/* ****************************************************************** * backprop.h ****************************************************************** */ #ifndef _BACKPROP_H_ #define _BACKPROP_H_
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cpp backprop.cpp

/* ****************************************************************** * backprop.cpp ****************************************************************** */ #include "StdAfx.h" #include
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h backprop.h

/* ****************************************************************** * backprop.h ****************************************************************** */ #ifndef _BACKPROP_H_ #define _BACKPROP_H
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java backprop.java

package com.digiburo.backprop1; import java.io.File; import java.io.FileInputStream; import java.io.FileOutputStream; import java.io.ObjectInputStream; import java.io.ObjectOutputStream; import java
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cpp backprop.cpp

/* ****************************************************************** * backprop.cpp ****************************************************************** */ #include "StdAfx.h" #include #
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h backprop.h

/* ****************************************************************** * backprop.h ****************************************************************** */ #ifndef _BACKPROP_H_ #define _BACKPROP_H_
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h backprop.h

#ifndef _BACKPROP_ #define _BACKPROP_ #define EPOCHS 3000 #define SAVE_WGTS_FREQ 50 #define DISPLAY_FREQ 10 #define NN_n_inp 3 #define DEFAULT_HIDDENS 4 #define NN_n_out 1 #defin
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c backprop.c

/************************************ Code for implementing the backpropagation algorithm for training a fully-connected MLP neural network with 1 layer of hidden units. Loosely translated fr