mlpack  2.0.1
ra_util.hpp
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1 
15 #ifndef __MLPACK_METHODS_RANN_RA_UTIL_HPP
16 #define __MLPACK_METHODS_RANN_RA_UTIL_HPP
17 
18 #include <mlpack/core.hpp>
19 
20 namespace mlpack {
21 namespace neighbor {
22 
23 class RAUtil
24 {
25  public:
35  static size_t MinimumSamplesReqd(const size_t n,
36  const size_t k,
37  const double tau,
38  const double alpha);
39 
49  static double SuccessProbability(const size_t n,
50  const size_t k,
51  const size_t m,
52  const size_t t);
53 
63  static void ObtainDistinctSamples(const size_t numSamples,
64  const size_t rangeUpperBound,
65  arma::uvec& distinctSamples);
66 };
67 
68 } // namespace neighbor
69 } // namespace mlpack
70 
71 #endif
Linear algebra utility functions, generally performed on matrices or vectors.
Include all of the base components required to write MLPACK methods, and the main MLPACK Doxygen docu...
static size_t MinimumSamplesReqd(const size_t n, const size_t k, const double tau, const double alpha)
Compute the minimum number of samples required to guarantee the given rank-approximation and success ...
static double SuccessProbability(const size_t n, const size_t k, const size_t m, const size_t t)
Compute the success probability of obtaining 'k'-neighbors from a set of size 'n' within the top 't' ...
static void ObtainDistinctSamples(const size_t numSamples, const size_t rangeUpperBound, arma::uvec &distinctSamples)
Pick up desired number of samples (with replacement) from a given range of integers so that only the ...
see subsection cli_alt_reg_tut Alternate DET regularization The usual regularized error f $R_ alpha(t)\f $of a node\f $t\f $is given by
Definition: det.txt:344