文件名称:Softmax_exercise
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2016-10-30
- 文件大小：
- 10.24mb
- 下载次数：
- 0次
- 提 供 者：
- 安*
- 相关连接：
- 无
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- 别用迅雷下载，失败请重下，重下不扣分！
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Softmax用于多分类问题，本例是将MNIST手写数字数据库中的数据0-9十个数字进行分类，其中训练样本有6万个，测试样本有1万个数字是0~9-Softmax for multi classification problems, the present case is the handwritten data MNIST digital 0-9, classification, training samples which have 60,000, there are 10,000 test samples digit 0 to 9
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下载文件列表
Softmax_exercise\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
................\.......\.ogistic\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
................\t10k-images.idx3-ubyte
................\t10k-labels.idx1-ubyte
................\train-images.idx3-ubyte
................\train-labels.idx1-ubyte
................\minFunc\logistic
................\minFunc
Softmax_exercise