[mlpack-git] master: Update documentation and use Train() not Estimate() for distributions. (e444bd0)

gitdub at big.cc.gt.atl.ga.us gitdub at big.cc.gt.atl.ga.us
Fri Dec 18 11:43:06 EST 2015


Repository : https://github.com/mlpack/mlpack

On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/5ba11bc90223b55eecd5da4cfbe86c8fc40637a5...df229e45a5bd7842fe019e9d49ed32f13beb6aaa

>---------------------------------------------------------------

commit e444bd07cd884a1fc44055e08ece20e419888ec0
Author: Ryan Curtin <ryan at ratml.org>
Date:   Wed Dec 16 21:02:00 2015 +0000

    Update documentation and use Train() not Estimate() for distributions.


>---------------------------------------------------------------

e444bd07cd884a1fc44055e08ece20e419888ec0
 src/mlpack/methods/hmm/hmm.hpp | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/mlpack/methods/hmm/hmm.hpp b/src/mlpack/methods/hmm/hmm.hpp
index de375da..da03d9b 100644
--- a/src/mlpack/methods/hmm/hmm.hpp
+++ b/src/mlpack/methods/hmm/hmm.hpp
@@ -35,12 +35,12 @@ namespace hmm /** Hidden Markov Models. */ {
  *   double Probability(const DataType& observation) const;
  *
  *   // Estimate the distribution based on the given observations.
- *   void Estimate(const std::vector<DataType>& observations);
+ *   void Train(const std::vector<DataType>& observations);
  *
  *   // Estimate the distribution based on the given observations, given also
  *   // the probability of each observation coming from this distribution.
- *   void Estimate(const std::vector<DataType>& observations,
- *                 const std::vector<double>& probabilities);
+ *   void Train(const std::vector<DataType>& observations,
+ *              const std::vector<double>& probabilities);
  * };
  * @endcode
  *
@@ -71,7 +71,7 @@ namespace hmm /** Hidden Markov Models. */ {
  * Once initialized, the HMM can evaluate the probability of a certain sequence
  * (with LogLikelihood()), predict the most likely sequence of hidden states
  * (with Predict()), generate a sequence (with Generate()), or estimate the
- * probabilities of each state for a sequence of observations (with Estimate()).
+ * probabilities of each state for a sequence of observations (with Train()).
  *
  * @tparam Distribution Type of emission distribution for this HMM.
  */



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