Method update

machine_learning/self_organizing_map.py:24–35

Update the winning vector. >>> SelfOrganizingMap().update([[1, 2, 3], [4, 5, 6]], [1, 2, 3], 1, 0.1) [[1, 2, 3], [3.7, 4.7, 6]]

(
        self, weights: list[list[int | float]], sample: list[int], j: int, alpha: float
    )

        return 0

    def update(
        self, weights: list[list[int | float]], sample: list[int], j: int, alpha: float
    ) -> list[list[int | float]]:
        """
        Update the winning vector.

        >>> SelfOrganizingMap().update([[1, 2, 3], [4, 5, 6]], [1, 2, 3], 1, 0.1)
        [[1, 2, 3], [3.7, 4.7, 6]]
        """
        for i in range(len(weights)):
            weights[j][i] += alpha * (sample[i] - weights[j][i])
        return weights


# Driver code