Metadata-Version: 2.1
Name: Dendrite-Neural-Networks
Version: 0.0.2
Summary: Dendrite-Neural-Networks is an implementation of processing units that performed classification using closed decision boundaries with only one neuron.
Home-page: UNKNOWN
Author: Rodrigo Román Godínez.
Author-email: rodrigo_0045@hotmail.com, rodrigo0045@gmail.com
License: UNKNOWN
Description: # Dendrite-Neural-Networks
        
        Dendrite-Neural-Networks is a Python library for dealing with closed boundary classification units, like Dendrite Morphological Neuron (DMN), Dendrite Ellipsoidal Neuron (DEN) and Dendrite Spherical Neuron (DSN).
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Dendrite-Neural-Networks.
        
        ```bash
        pip install Dendrite-Neural-Networks
        ```
        
        ## Usage
        
        ```python
        from DEN import DENlayer
        from DMN import DMNlayer
        from DSN import DSNlayer
        
        from PreTrain.HpC import HSpC
        from PreTrain.HpC import HEpC
        from PreTrain.HpC import HBpC
        
        from PreTrain.kmeans import bkmeans
        from PreTrain.kmeans import ekmeans
        from PreTrain.kmeans import skmeans
        
        # returns 'array' with the propose initial parameters
        #x: Input pattern
        #y: Labels
        dendrites  = HBpC.HBpC(x,y,0.0001)
        dendrites  = HEpC.HEpC(x,y)
        dendrites  = HSpC.HSpC(x,y,0.0001)
        dendrites  = bkmeans.bkmeans(x,y,[3,3,3],0.01)
        dendrites  = ekmeans.ekmeans(x,y,[3])
        dendrites  = skmeans.skmeans(x,y,[2],0.01)
        
        
        # It's an implementation of a modified Keras layer
        DMNlayer(2,dendrites, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        DENlayer(2,dendrites, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        DSNlayer(2,dendrites, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        
        # It's an implementation of a modified Keras layer. For random initialization of parameters
        DMNlayer(2, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        DENlayer(2, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        DSNlayer(2, activation = "sigmoid", input_shape = (np.shape(x)[1],)))
        ```
        
        ## Contributing
        Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
        
        Please make sure to update tests as appropriate.
        
        ## License
        [GNU GPLv3](https://choosealicense.com/licenses/gpl-3.0/)
Platform: UNKNOWN
Description-Content-Type: text/markdown
