adaption

问题 In tutorials it has written this command: ~~~ ./bw \ -hmmdir en-us \ -moddeffn en-us/mdef.txt \ -ts2cbfn .ptm. \ -feat 1s_c_d_dd \ -svspec 0-12/13-25/26-38 \ -cmn current \ -agc none \ -dictfn cmudict-en-us.dict \ -ctlfn arctic20.fileids \ -lsnfn arctic20.transcription \ -accumdir . ~~~ But I checked my feat.params and it has this content: ~~~ -lowerf 130 -upperf 6800 -nfilt 25 -transform dct -lifter 22 -feat 1s_c_d_dd -svspec 0-12/13-25/26-38 -agc none -cmn current -varnorm no -model ptm

问题 What is the best way to adapt a neural network after its initial training? I.e. I want to do some image recognition and the network should get better the more new pictures I present it. That could be done with reinforced learning but for a fast progress at the beginning I want to use back propagation. Is it possible to update a network? And what about creating new categories later on? Is there another way than retraining it with the complete dataset since that would take a lot of time. Sorry