In the example below we've created a simple Logic And using our class
>>> from neurallogic import Neural
>>> bias = -0.2
>>> weights = [-0.1 , 0.2, 0.2]
>>> import numpy as np
>>> dataset = np.array([
... [1,0,0],
... [1,0,1],
... [1,1,0],
... [1,1,1]
... ])
>>> neural = Neural(weights, bias, dataset)
>>> neural.logit
array([[0.42555748],
[0.47502081],
[0.47502081],
[0.52497919]])
>>> neural.__converted__()
array([[0.],
[0.],
[0.],
[1.]])Here's another example in creating a simple Logic Or using our class
>>> from neurallogic import Neural
>>> import numpy as np
>>> bias = -0.1
>>> weights = [-0.1, 0.7,0.7]
>>> dataset = np.array([
... [1,0,0],
... [1,0,1],
... [1,1,0],
... [1,1,1]
... ])
>>> neural = Neural(weights, bias, dataset)
>>> neural.logit
array([[0.450166 ],
[0.62245933],
[0.62245933],
[0.76852478]])
>>> neural.__converted__()
array([[0.],
[1.],
[1.],
[1.]])
>>>