"New Neural" is an Open Source neural network engine project for the MetaTrader 5 platform. - page 18
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In general, ideally, you should get something like this http://www.peltarion.com/products/synapse/comparison.php.
At least you can be guided by what inquisitive mind of a non-programmer user may want. :)
Ouch ! That's not what I know ?
Unless you can guess ... I think I've only told Victor so far.
Are you intriguing, bragging, inviting ? // underline as appropriate
per worker's request :)
I'll tell you right off the bat -- I don't think you'd be interested.
In general, ideally, it should be something like this http://www.peltarion.com/products/synapse/comparison.php
Uh-huh. You're a killer. The license costs 1,000 grivnas... You've got a good point :)
In general, ideally, you should get something like this http://www.peltarion.com/products/synapse/comparison.php.
At least you can be guided by what inquisitive mind of a non-programmer user may want. :)
Now explain me a lamer, which of these mats are neural network types, types of learning and what are trademarks:
Data input------------------Text
Image
Signal generator
SQL database
User script
User custom built
Data output------------------
Text
SQL database
User custom built
Preprocessing---------------
Data rearrangement
PCA
Outlier removal
Query-based filtering
Statistical
User script
Interactive visualization
Postprocessing-------------
Error analysis and tracing
Confidece analysis
Sensitivity analysis
Real-time testing
Adaptive paradigms-------
Ststic neural networks
Dynamic neural networks
Kernel machines
Bayesian methods
LSTM
Fuzzy logic
Optimazation paradigms-
Genetic algorithms
Particle swarm
Monte carlo
Architectures---------------
MLP
Generalized MLP
Modular netwoks
Self-organizing maps
Neural gas
Competitive learning
Hebbian
FFCPA
Radial basis networks
LSTM
Time lagged recurrent
Partially recurrent
Wavelet networks
Fully recurrent
Neuro-fuzzy
Support Vector Machines
Custom architectures
System design---------------
Component based
Plug-in based xml-ph-NET compliant
User interface----------------
Graphical construction
Scalable user interface
Block embedded GUI
Deployment-------------------
Solutions are deployable
.NET compatible components
Reusable components
Scalable deployment
Royalty free use of deployed systems
Now explain to me, as a lamer, which of these mate types of neural networks, types of learning and what are trademarks:
Generalized MLP
Modular netwoks -- ugh
Self-organising maps
Neural gas
Competitive learning -- unclear
Hebbian -- dunno, but if what I think is interesting
FFCPA -- dunno
Radial basis networks
LSTM -- ugh
Time lagged recurrent
Partially recurrent
Fully recurrent I wonder how one differs from the other.
Wavelet networks - I don't know
Neuro-fuzzy - this is probably what I was talking about.
Support Vector Machines - dunno
xz -- something I'm not familiar with
Learning/optimization algorithms:
Network Types:
At least some kind of battle plan.
By the way, why don't they have BeckProp? Or did I misunderstand something.
There's only Genetics, Bee Swarm and Montecarlo?