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| *********************************Support neural networks types********************************* **Single layer perceptron** - create function: `neurolab.net.newp() <http://packages.python.org/neurolab/lib.html#neurolab.net.newp>`_ - example of use: `newp <http://packages.python.org/neurolab/ex_newp.html>`_ - default train function: `neurolab.train.train_delta() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_delta>`_ - support train functions: train_gd, train_gda, train_gdm, train_gdx, train_rprop, train_bfgs, train_cg **Multilayer feed forward perceptron** - create function: `neurolab.net.newff() <http://packages.python.org/neurolab/lib.html#neurolab.net.newff>`_ - example of use: `newff <http://packages.python.org/neurolab/ex_newff.html>`_ - default train function: `neurolab.train.train_gdx() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_gdx>`_ - support train functions: train_gd, train_gda, train_gdm, train_rprop, train_bfgs, train_cg **Competing layer (Kohonen Layer)** - create function: `neurolab.net.newc() <http://packages.python.org/neurolab/lib.html#neurolab.net.newc>`_ - example of use: `newc <http://packages.python.org/neurolab/ex_newc.html>`_ - default train function: `neurolab.train.train_cwta() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_cwta>`_ - support train functions: train_wta **Learning Vector Quantization (LVQ)** - create function: `neurolab.net.newlvq() <http://packages.python.org/neurolab/lib.html#neurolab.net.newlvq>`_ - example of use: `newlvq <http://packages.python.org/neurolab/ex_newlvq.html>`_ - default train function: `neurolab.train.train_lvq() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_lvq>`_ **Elman Recurrent network** - create function: `neurolab.net.newelm() <http://packages.python.org/neurolab/lib.html#neurolab.net.newelm>`_ - example of use: `newelm <http://packages.python.org/neurolab/ex_newelm.html>`_ - default train function: `neurolab.train.train_gdx() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_gdx>`_ - support train functions: train_gd, train_gda, train_gdm, train_rprop, train_bfgs, train_cg **Hopfield Recurrent network** - create function: `neurolab.net.newhop() <http://packages.python.org/neurolab/lib.html#neurolab.net.newhop>`_ - example of use: `newhop <http://packages.python.org/neurolab/ex_newhop.html>`_ **Hemming Recurrent network** - create function: `neurolab.net.newhem() <http://packages.python.org/neurolab/lib.html#neurolab.net.newhem>`_ - example of use: `newhem <http://packages.python.org/neurolab/ex_newhem.html>`_ | ||
| ********************************* | ||
| Support neural networks types | ||
| ********************************* | ||
|
|
||
| **Single layer perceptron** | ||
| - create function: `neurolab.net.newp() <http://packages.python.org/neurolab/lib.html#neurolab.net.newp>`_ | ||
| - example of use: `newp <http://packages.python.org/neurolab/ex_newp.html>`_ | ||
| - default train function: `neurolab.train.train_delta() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_delta>`_ | ||
| - support train functions: train_gd, train_gda, train_gdm, train_gdx, train_rprop, train_bfgs, train_cg | ||
|
|
||
| **Multilayer feed forward perceptron** | ||
| - create function: `neurolab.net.newff() <http://packages.python.org/neurolab/lib.html#neurolab.net.newff>`_ | ||
| - example of use: `newff <http://packages.python.org/neurolab/ex_newff.html>`_ | ||
| - default train function: `neurolab.train.train_bfgs() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_bfgs>`_ | ||
| - support train functions: train_gd, train_gda, train_gdm, train_rprop, train_bfgs, train_cg | ||
|
|
||
| **Competing layer (Kohonen Layer)** | ||
| - create function: `neurolab.net.newc() <http://packages.python.org/neurolab/lib.html#neurolab.net.newc>`_ | ||
| - example of use: `newc <http://packages.python.org/neurolab/ex_newc.html>`_ | ||
| - default train function: `neurolab.train.train_cwta() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_cwta>`_ | ||
| - support train functions: train_wta | ||
|
|
||
| **Learning Vector Quantization (LVQ)** | ||
| - create function: `neurolab.net.newlvq() <http://packages.python.org/neurolab/lib.html#neurolab.net.newlvq>`_ | ||
| - example of use: `newlvq <http://packages.python.org/neurolab/ex_newlvq.html>`_ | ||
| - default train function: `neurolab.train.train_lvq() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_lvq>`_ | ||
|
|
||
| **Elman Recurrent network** | ||
| - create function: `neurolab.net.newelm() <http://packages.python.org/neurolab/lib.html#neurolab.net.newelm>`_ | ||
| - example of use: `newelm <http://packages.python.org/neurolab/ex_newelm.html>`_ | ||
| - default train function: `neurolab.train.train_gdx() <http://packages.python.org/neurolab/lib.html#neurolab.train.train_gdx>`_ | ||
| - support train functions: train_gd, train_gda, train_gdm, train_rprop, train_bfgs, train_cg | ||
|
|
||
| **Hopfield Recurrent network** | ||
| - create function: `neurolab.net.newhop() <http://packages.python.org/neurolab/lib.html#neurolab.net.newhop>`_ | ||
| - example of use: `newhop <http://packages.python.org/neurolab/ex_newhop.html>`_ | ||
| **Hemming Recurrent network** | ||
| - create function: `neurolab.net.newhem() <http://packages.python.org/neurolab/lib.html#neurolab.net.newhem>`_ | ||
| - example of use: `newhem <http://packages.python.org/neurolab/ex_newhem.html>`_ |