Modified Linear Regression to work on OLS, fixes #8847

neural_network/activation_functions/bipolar_binary_step.py

@@ -0,0 +1,35 @@
+"""
+This script demonstrates the implementation of the Bipolar Binary Step function.
+
+It's an activation function in which the neuron outputs 1 if the input is positive
+or 0, else outputs -1 if the input is negative.
+
+It's a simple activation function which is mentioned in this wikipedia article:
+https://en.wikipedia.org/wiki/Activation_function
+"""
+
+import numpy as np
+
+
+def bipolar_binary_step(vector: np.ndarray) -> np.ndarray:
+ """
+ Implements the binary step function
+
+ Parameters:
+ vector (ndarray): A vector that consists of numeric values
+
+ Returns:
+ vector (ndarray): Input vector after applying binary step function
+
+ >>> vector = np.array([-1.2, 0, 2, 1.45, -3.7, 0.3])
+ >>> bipolar_binary_step(vector) # doctest: +NORMALIZE_WHITESPACE
+ array([-1, 1, 1, 1, -1, 1])
+ """
+
+ return np.where(vector >= 0, 1, -1)
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()