python中kmeans中k怎么取值_kmeans在Python中的用法

我正在考虑使用OpenCV的Kmeans实现&＃xff0c;因为它说更快。。。

现在我使用的是cv2包和kmeans函数

我无法理解参考资料中的参数说明&＃xff1a;Python: cv2.kmeans(data, K, criteria, attempts, flags[, bestLabels[, centers]]) → retval, bestLabels, centers

samples – Floating-point matrix of input samples, one row per sample.

clusterCount – Number of clusters to split the set by.

labels – Input/output integer array that stores the cluster indices for every sample.

criteria – The algorithm termination criteria, that is, the maximum number of iterations and/or the desired accuracy. The accuracy is specified as criteria.epsilon. As soon as each of the cluster centers moves by less than criteria.epsilon on some iteration, the algorithm stops.

attempts – Flag to specify the number of times the algorithm is executed using different initial labelings. The algorithm returns the labels that yield the best compactness (see the last function parameter).

flags –

Flag that can take the following values:

KMEANS_RANDOM_CENTERS Select random initial centers in each attempt.

KMEANS_PP_CENTERS Use kmeans&＃43;&＃43; center initialization by Arthur and Vassilvitskii [Arthur2007].

KMEANS_USE_INITIAL_LABELS During the first (and possibly the only) attempt, use the user-supplied labels instead of computing them from the initial centers. For the second and further attempts, use the random or semi-random centers. Use one of KMEANS_*_CENTERS flag to specify the exact method.

centers – Output matrix of the cluster centers, one row per each cluster center.

参数flags[, bestLabels[, centers]])是什么意思&＃xff1f;那他的那个呢&＃xff1a;→ retval, bestLabels, centers&＃xff1f;

这是我的代码&＃xff1a;import cv, cv2

import scipy.io

import numpy

# read data from .mat file

mat &＃61; scipy.io.loadmat(&＃39;...&＃39;)

keys &＃61; mat.keys()

values &＃61; mat.viewvalues()

data_1 &＃61; mat[keys[0]]

nRows &＃61; data_1.shape[1]

nCols &＃61; data_1.shape[0]

samples &＃61; cv.CreateMat(nRows, nCols, cv.CV_32FC1)

labels &＃61; cv.CreateMat(nRows, 1, cv.CV_32SC1)

centers &＃61; cv.CreateMat(nRows, 100, cv.CV_32FC1)

#centers &＃61; numpy.

for i in range(0, nCols):

for j in range(0, nRows):

samples[j, i] &＃61; data_1[i, j]

cv2.kmeans(data_1.transpose,

100,

criteria&＃61;(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_MAX_ITER, 0.1, 10),

attempts&＃61;cv2.KMEANS_PP_CENTERS,

flags&＃61;cv2.KMEANS_PP_CENTERS,

)

我遇到这样的错误&＃xff1a;flags&＃61;cv2.KMEANS_PP_CENTERS,

TypeError: is not a numpy array

我应该如何理解参数列表和cv2.kmeans的用法&＃xff1f;谢谢