def cluster_distance(cluster1, cluster2, distance_agg=min):
"""compute all the pairwise distances between cluster1 and cluster2
and apply distance_agg to the resulting list"""
return distance_agg([
algebra.distance(input1, input2) for input1 in get_values(cluster1)
for input2 in get_values(cluster2)
])
def knn_classify(k, labeled_points, new_point):
"""each labeled point should be a pair (point, label)"""
by_distance = sorted(labeled_points, key=lambda (point, _): algebra.distance(point, new_point))
k_nearest_labels = [label for _, label in by_distance[:k]]
return majority_vote(k_nearest_labels)
def knn_classify(k, labeled_points, new_point):
"""each labeled point should be a pair (point, label)"""
by_distance = sorted(labeled_points,
key=lambda
(point, _): algebra.distance(point, new_point))
k_nearest_labels = [label for _, label in by_distance[:k]]
return majority_vote(k_nearest_labels)
def cluster_distance(cluster1, cluster2, distance_agg=min):
"""compute all the pairwise distances between cluster1 and cluster2
and apply distance_agg to the resulting list"""
return distance_agg([algebra.distance(input1, input2)
for input1 in get_values(cluster1)
for input2 in get_values(cluster2)])
