feat: add maxout activation function

neural_network/activation_functions/maxout.py

@@ -0,0 +1,44 @@
+"""
+Maxout activation function
+
+Use Case: Maxout allows for more flexibility than traditional
+activation functions like ReLU and can improve model capacity.
+
+For more detailed information, you can refer to the following link:
+https://arxiv.org/abs/1302.4389
+"""
+
+import numpy as np
+
+
+def maxout(vector: np.ndarray) -> np.ndarray:
+    """
+    Implements the Maxout Activation Function.
+
+    Parameters:
+        vector (np.ndarray): The input array for Maxout activation.
+
+    Returns:
+        np.ndarray: The output of Maxout activation applied to pairs of inputs.
+
+    Formula: f(x) = max(x_1, x_2)
+
+    Examples:
+    >>> maxout(np.array([[2., -3.], [-1., 4.]]))
+    array([[2.],
+           [4.]])
+
+    >>> maxout(np.array([[5, -5], [3, -3]]))
+    array([[5],
+           [3]])
+
+    """
+    return np.maximum(
+        vector[:, : vector.shape[1] // 2], vector[:, vector.shape[1] // 2 :]
+    )
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()