Method __init__

mla/knn.py:12–26

Base class for Nearest neighbors classifier and regressor. Parameters ---------- k : int, default 5 The number of neighbors to take into account. If 0, all the training examples are used. distance_func : function, default euclidean distance

(self, k=5, distance_func=euclidean)

class KNNBase(BaseEstimator):
    def __init__(self, k=5, distance_func=euclidean):
        """Base class for Nearest neighbors classifier and regressor.

        Parameters
        ----------
        k : int, default 5
            The number of neighbors to take into account. If 0, all the
            training examples are used.
        distance_func : function, default euclidean distance
            A distance function taking two arguments. Any function from
            scipy.spatial.distance will do.
        """

        self.k = None if k == 0 else k  # l[:None] returns the whole list
        self.distance_func = distance_func

    def aggregate(self, neighbors_targets):
        raise NotImplementedError()