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  1. How to sample large database and implement K-means and K-nn ... A randomly sample the SOURCE database to create a ... tagged r machine-learning large-data k-means knn ...
    stackoverflow.com/questions/13672340/​how-to-sample-large... - Cached
  2. How to sample large database and implement K-means and K-nn in R?-4. R k-means clustering data. 1. Determining optimum number of clusters for k-means with a large ...
    stack overflow.com/questions/18042290/​implementing-the... - Cached

  3. K-nearest neighbors algorithm - Wikipedia, the free encyclopedia

    Example of k-NN classification. The test sample ... makes kNN computationally tractable even for large ... on raw data prior to applying K-NN algorithm ...
    en.wikipedia.org/wiki/K-nearest_ ​neighbor_algorithm - Cached
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  4. k- means clustering - Wikipedia, the free encyclopedia

    ... is rather easy to implement and apply even on large data ... a K-Means implementation; R ... for large scale data. Weka contains k-means and ...
    en.wikipedia.org/wiki/K-means_​clustering - Cached
  5. Adobe PDF
    operation can be successfully applied to implement data ... k-means and k-medoid clustering, sample assessment ... For the k-nn join RS, we denote the data set R for ...
    www.dbs.informatik.uni-muenchen.de/​~boehm/publications...
  6. Adobe PDF
    ... k-means and k-medoid clus tering, sample ... it is possible to replace a large number of k-nn ... For the k-nn join RS, we denote the data set R for ...
    www.dbs.informatik.uni-muenchen.de/​~boehm/publications...
  7. Adobe PDF
    k-nearest neighbour classification, k-means clustering, sample ... it is possible to replace a large number of k-nn queries ... k-nn S, we denote the data set R for ...
    www.dbs.ifi.lmu.de/Publikationen/Boehm/†‹KAIS_04.pdf
  8. If the number of data points is very large, ... knn algorithm in R language and how to ... work using k-means model and k-NN model in ...
    saravananthirumuruganathan.wordpress.com​/2010/05/17/a... - Cached
  9. Data Mining Algorithms In R ... it is used solely to populate a sample of the search space with ... This is problematic for datasets with a large number of ...
    en.wikibooks.org/wiki/Data_Mining_​Algorithms_In_R/... - Cached
  10. Adobe PDF
    ... have shown how to scale k-means clustering to very large data sets ... a random sample of data ... a k-means problem on a set of points in Rd for ...
    www.cs.umd.edu/~mount/Projects/KMeans/​pami02.pdf