Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
310 views
in Technique[技术] by (71.8m points)

python - How do you optimize this code for nn prediction?

How do you optimize this code? At the moment it is running to slow for the amount of data that goes through this loop. This code runs 1-nearest neighbor. It will predict the label of the training_element based off the p_data_set

#               [x] ,           [[x1],[x2],[x3]],    [l1, l2, l3]
def prediction(training_element, p_data_set, p_label_set):
    temp = np.array([], dtype=float)
    for p in p_data_set:
        temp = np.append(temp, distance.euclidean(training_element, p))

    minIndex = np.argmin(temp)
    return p_label_set[minIndex]
See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

Use a k-D tree for fast nearest-neighbour lookups, e.g. scipy.spatial.cKDTree:

from scipy.spatial import cKDTree

# I assume that p_data_set is (nsamples, ndims)
tree = cKDTree(p_data_set)

# training_elements is also assumed to be (nsamples, ndims)
dist, idx = tree.query(training_elements, k=1)

predicted_labels = p_label_set[idx]

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

1.4m articles

1.4m replys

5 comments

57.0k users

...