New article Deep neural network with Stacked RBM. Self-training, self-control has been published:
This article is a continuation of previous articles on deep neural network and predictor selection. Here we will cover features of a neural network initiated by Stacked RBM, and its implementation in the "darch" package.
I recall that DN_SRBM consists of n-number of RBM that equals the
number of hidden layers of neural network and, basically, the neural
network itself. Training comprises two stages.
stage involves PRE-TRAINING. Every RBM is systematically trained without
a supervisor on the input set (without target). After this weight of
hidden layers, RBM are transferred to relevant hidden layers of neural
The second stage involves FINE-TUNING, where neural
network is trained with a supervisor. Detailed information about it was
provided in the previous article, so we don't have to repeat ourselves
here. I will simply mention that unlike the "deepnet" package that we
have used in the previous article, the "darch" package helps us to
implement wider opportunities in building and tuning the model. More
details will be provided when creating the model. Fig. 1 shows the
structure and the training process of DN_SRBM
Fig. 1. Structure of DN SRBM
Author: Vladimir Perervenko
very very very good article
many thanks for your beautiful contribution
never try the R package before, i try the mql4 expert, at first everything ok, but 3 minutes after the launch (during teaching phase), rterm crash !
i will investigate why ... if you have some ideas ?
theoretically a very good article,
but practically useless because the application is not running, and advice is not to be expected...
I would like to correct my opinion,
after downloading RStudio, a third-party interface for R, and donwloading all needed packages its running without Problems.
RStudio has the advantage that all dependencies are installed automatically.
Rterm falls mostly because of lack of necessary libraries and affiliated libraries.There will be questions, ask.Good luck