文件名称:stacked-autoencoder
- 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：
- 14.63mb
- 下载次数：
- 0次
- 提 供 者：
- 安*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
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基于两层的层叠自编码的深度学习模型，前两层用于特征提取，再加一个Softmax分类器用于分类-Two stacked the depth of learning coding model based on the first two levels for feature extraction, coupled with a classifier for classifying Softmax
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下载文件列表
stacked autoencoder\checkNumericalGradient.m
...................\checkStackedAECost.m
...................\computeNumericalGradient.m
...................\display_network.m
...................\feedForwardAutoencoder.m
...................\initializeParameters.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
...................\params2stack.m
...................\softmaxCost.m
...................\softmaxPredict.m
...................\softmaxTrain.m
...................\sparseAutoencoderCost.m
...................\stack2params.m
...................\stackedAECost.m
...................\stackedAEExercise.m
...................\stackedAEPredict.m
...................\step2.mat
...................\step3.mat
...................\step4.mat
...................\step5.mat
...................\t10k-images.idx3-ubyte
...................\t10k-labels.idx1-ubyte
...................\train-images.idx3-ubyte
...................\train-labels.idx1-ubyte
...................\minFunc\logistic
...................\minFunc
stacked autoencoder