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BOWKMeansTrainer constructor

asked 2017-11-29 06:40:03 -0500

sama_z gravatar image

updated 2017-11-29 06:43:53 -0500

Hi, I have a question regarding BOWKMeansTrainer constructor. Would anyone please tell me what are the parameters of the constructor? I had a look at opencv document, but I could not find any useful information.

So far I know it has these parameters BOWKMeansTrainer::BOWKMeansTrainer(int clusterCount, const TermCriteria& termcrit=TermCriteria(), int attempts=3, int flags=KMEANS_PP_CENTERS ) And I know clusterCount is the dictionary size/number of clusters. I also guess that attempts is the K parameter for K-Mean. It means if it's 3 the trainer will calculate 3-Means/3 steps.

But I want to know what are the rests task?

Many thanks in advance,

Bests,

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answered 2017-11-29 07:32:27 -0500

arigarcia gravatar image

See:

  • K is clusters number in TermCriteria you can to define iterations numbers and rules for terminations, for instance TermCriteria (EPS + MAX_ITER, 1000, 0.1), so when you iteration = MAX_ITER = 1000 or epsilon = 0.1 your running will stop
  • flag KMEANS_PP_CENTERS says that will run kmean++ algorithm;
  • attemps: number of initializations of the algorithm

See example in https://docs.opencv.org/3.3.0/de/d63/....

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Thanks for the comment. Could you explain more about iteration? which iteration you mean? Is this means value from each clustering level? I know so far how K-means is working, but what is K-means plus plus? What are the differences between them?

sama_z gravatar imagesama_z ( 2017-11-29 08:27:14 -0500 )edit
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Asked: 2017-11-29 06:40:03 -0500

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Last updated: Nov 29 '17