The weighted k-nearest neighbors (k-NN) classification algorithm is a relatively simple technique to predict the class of an item based on two or more numeric predictor variables. For example, you ...

print("\nEnd k-means demo ") if __name__ == "__main__": main() The demo uses Python 3.5 in the Anaconda 4.1.1 distribution. The program imports the NumPy package to gain access to array functionality.

Here is an array. Oh, you need to make sure you have the numpy python module loaded. If you just use plain python, there is no array. Both the visual module and the pylab module load numpy.