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* Add binary step activation function * fix: ruff line too long error * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * refactor: add link to directory * revert: add link to directory * fix: algorithm bug and docs * Update neural_network/activation_functions/binary_step.py * fix: ruff line too long error --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
37 lines
858 B
Python
37 lines
858 B
Python
"""
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This script demonstrates the implementation of the Binary Step function.
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It's an activation function in which the neuron is activated if the input is positive
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or 0, else it is deactivated
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It's a simple activation function which is mentioned in this wikipedia article:
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https://en.wikipedia.org/wiki/Activation_function
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"""
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import numpy as np
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def binary_step(vector: np.ndarray) -> np.ndarray:
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"""
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Implements the binary step function
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Parameters:
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vector (ndarray): A vector that consists of numeric values
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Returns:
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vector (ndarray): Input vector after applying binary step function
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>>> vector = np.array([-1.2, 0, 2, 1.45, -3.7, 0.3])
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>>> binary_step(vector)
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array([0, 1, 1, 1, 0, 1])
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"""
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return np.where(vector >= 0, 1, 0)
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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