Radial Basis Function Networks

A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. It is a linear combination of radial basis functions. They are used in function approximation, time series prediction, and control.

from miml import datasets
from miml.regression import RBFNetwork

fn = os.path.join(datasets.get_data_home(), 'regression',
    'diabetes.csv')
df = DataFrame.read_table(fn, delimiter=',',
    format='%64f', index_col=0)

x = df.values
y = array(df.index.data)

model = RBFNetwork(ncenters=10)
model.fit(x, y)

print(model.predict(x[:10,:]))

>>> run script...
array([184.24810109990693, 56.45535138916093, 84.27105955131076, 263.694752740725, 89.74377301427681, 120.98329139858919, 150.4263763674829, 79.06152761584222, 108.62840807898104, 94.94832854058508])