Description: Automatic linear encoder decoder mainly on account of sparse autocoder last layer output if sigmoid function, since learning sparse automatic encoder output is equal to input range simoid function between [0,1], which must also be asked to enter [0,1], which is the input feature hidden restrictions, in order to lift this restriction, we can make the last layer of a linear function and a z
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linear_autoencoder\checkNumericalGradient.m
..................\computeNumericalGradient.m
..................\displayColorNetwork.m
..................\initializeParameters.m
..................\linearDecoderExercise.m
..................\sparseAutoencoderLinearCost.m
linear_autoencoder