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
