Man pages for deeplearning
An Implementation of Deep Neural Network for Regression and Classification

applyDropoutMaskApplies the given dropout mask to the given data row-wise.
ARCalculates the Accuracy Ratio of a classifier
AR.DArchCalculates the Accruacy Ratio of a given set of probability
AR.defaultCalculates the Accruacy Ratio of a given set of probability
AR.numericCalculates the Accruacy Ratio of a given set of probability
backpropagate_delta_bnCalculates the delta functions using backpropagation
batch_normalizationBatch Normalization Function that normalizes the input before...
batch_normalization_differentialFunction that calcualtes the differentials in the batch...
calcualte_population_mu_sigmaCalculates the mu and sigmas of a darch instance
classification_errorCalculates the classification error
convert_categoricalData proprosess function that covnerts a categorical input to...
crossEntropyErrCalculates the cross entropy error
finetune_SGD_bnUpdates a deep neural network's parameters using stochastic...
generateDropoutMaskGenerates the dropout mask for the deep neural network
generateDropoutMasksForDarchGenerates dropout masks for dnn
matMultCalculates the outer product of two matricies
meanSquareErrCalculates the mean squared error
new_dnnCreats a new instance of darch class
print_weightPrints out the weight of a deep neural network
rectified_linear_unit_functionRectified Linear Unit Function
reset_population_mu_sigmaResets the mu and sigmas of a darch instance to 0 and 1
rsqCalculate the RSQ of a regression model Utilitiy function...
rsq.DArchUtilitiy function that calcualtes RSQ of a DArch instance
rsq.lmUtilitiy function that calcualtes RSQ of a linear model
run_dnnExecution function that runs in the batch normalization mode
train_dnnTrain a deep neural network
verticalizeCreates a matrix by repeating a row vector N times
deeplearning documentation built on Jan. 15, 2017, 9:52 a.m.