深度学习教程中关于softmax regression的练习代码我要分享

Deep learning tutorial about softmax regression practice code

斯坦福 深度学习 softmax-egression

关注次数: 384

下载次数: 0

文件大小: 78KB

代码分类: 其他

开发平台: matlab

下载需要积分: 1积分

版权声明:如果侵犯了您的权益请与我们联系,我们将在24小时内删除。

代码描述

中文说明:

斯坦福深度学习教程中关于softmax regression的练习代码,源代码中需要补全的地方,全部把代码补完整,把手写体识别的数据库放到路径下,可以直接运行。


English Description:

Stanford deep learning tutorial about softmax regression practice code, source code completion are needed, fill all the code complete, the handwriting recognition database on a path that can be run directly.


代码预览

Exercise5 Softmax Regression

............................\computeNumericalGradient.m

............................\loadMNISTImages.m

............................\loadMNISTLabels.m

............................\minFunc

............................\.......\ArmijoBacktrack.m

............................\.......\autoGrad.m

............................\.......\autoHess.m

............................\.......\autoHv.m

............................\.......\autoTensor.m

............................\.......\callOutput.m

............................\.......\conjGrad.m

............................\.......\dampedUpdate.m

............................\.......\example_minFunc.m

............................\.......\example_minFunc_LR.m

............................\.......\isLegal.m

............................\.......\lbfgs.m

............................\.......\lbfgsC.c

............................\.......\lbfgsC.mexa64

............................\.......\lbfgsC.mexglx

............................\.......\lbfgsC.mexmac

............................\.......\lbfgsC.mexmaci

............................\.......\lbfgsC.mexmaci64

............................\.......\lbfgsC.mexw32

............................\.......\lbfgsC.mexw64

............................\.......\lbfgsUpdate.m

............................\.......\logistic

............................\.......\........\LogisticDiagPrecond.m

............................\.......\........\LogisticHv.m

............................\.......\........\LogisticLoss.m

............................\.......\........\mexutil.c

............................\.......\........\mexutil.h

............................\.......\........\mylogsumexp.m

............................\.......\........\repmatC.c

............................\.......\........\repmatC.dll

............................\.......\........\repmatC.mexglx

............................\.......\........\repmatC.mexmac

............................\.......\mchol.m

............................\.......\mcholC.c

............................\.......\mcholC.mexmaci64

............................\.......\mcholC.mexw32

............................\.......\mcholC.mexw64

............................\.......\mcholinc.m

............................\.......\minFunc.m

............................\.......\minFunc_processInputOptions.m

............................\.......\polyinterp.m

............................\.......\precondDiag.m

............................\.......\precondTriu.m

............................\.......\precondTriuDiag.m

............................\.......\rosenbrock.m

............................\.......\taylorModel.m

............................\.......\WolfeLineSearch.m

............................\softmaxCost.m

............................\softmaxExercise.m

............................\softmaxPredict.m

............................\softmaxTrain.m