def __init__(self, vso, metric): NearestNeighbors.__init__(self, algorithm='auto', metric=metric_internal(metric)) self.original_metric = metric self.vso = vso self.concepts = tuple(vso.keys()) self.concept_vectors = list(vso.values()) self.fit(metric_norm(metric, self.concept_vectors))
def __init__(self, n_neighbors=5, metric="dtw", metric_params=None, n_jobs=None, verbose=0): NearestNeighbors.__init__(self, n_neighbors=n_neighbors, algorithm='brute') self.metric = metric self.metric_params = metric_params self.n_jobs = n_jobs self.verbose = verbose
def __init__(self, n_neighbors=5, metric="dtw", metric_params=None): NearestNeighbors.__init__(self, n_neighbors=n_neighbors, algorithm='brute') self.metric = metric self.metric_params = metric_params
def __init__(self, k, distance_threshold=1.0): NearestNeighbors.__init__(self, k) self.distance_threshold = distance_threshold