Implementation of a Radial Basis Network
Project description
RBasisPy
RBasisPy is a library that allows you to implement a Radial Basis Network in Python. This library has 3 radial basis function that can be use in the hidden layer of the network.
How to install RBasisPy?
It can be installed from terminal using pip: pip install RBasisPy
License
License for RBasisPy is GNU GPLv3.
RBasisPy documentation
Once the library is installed, it is necessary to call the network module: from RBasisPy import rbn, rbn is the Radial Basis Network and can be instaced with two parameters: K and f, K means numbers of units in the hidden layer and f the radial basis function.
Parameters
- K:
numbers of units in the hidden layer. - f:
{'gaussian', 'inv_sqr', 'inv_mul'} default='gaussian''gaussian': Gaussian function. 'inv_sqr': Inverse Quadratic function. 'inv_mul': Inverse Multiquadratic function.
Methods
- fit(X, y): fit the model, X: input data with shape (number of samples, number of features). Y: target vector with shape(n_samples).
- predict(X): predict X using the RBN.
Contact
- E-mail: michael.guzman.personal@gmail.com
- LinkedIn: Click here
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