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...
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
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 &#39;k&#39;-neighbors from a set of size &#39;n&#39; within the top &#39;t&#39; ...
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 ...