KSquare Utilities
KKMLVariables.h
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1 #if !defined(_KKMLVARIABLES_)
2 #define _KKMLVARIABLES_
3 
4 
5 
6 
7 /**
8  *@namespace KKMLL
9  *@brief This library provides data structures that support Machine Learning functionality.
10  *@details There are several classes defined in this library but the central ones that should be understood are
11  * MLClass, FeatureVector, Model, FileDesc, and Attribute. there is support for reading and writing several
12  * feature Data file formats C45 probably being the most well known.<p>
13  */
14 
15 namespace KKMLL
16 {
17  /**
18  *@class Variables
19  *@brief Variables that specific to the Machine Learning Library.
20  *@details All methods in this library are to use these variables to locate files and directories that they need.
21  */
23  {
24  public:
25  KKMLVariables ();
26  ~KKMLVariables ();
27 
28  static KKStr TempDir (); /**< Directory where we can put temporary files into. */
29  static KKStr TrainingLibrariesDir (); /**< Directory where training library directories will be under. */
30  static KKStr TrainingModelsDir (); /**< Directory where all Training Model Configuration files are stored. */
31 
32  static void SetMachineLearninigHomeDir (const KKStr& _machineLearningHomeDir);
33 
34  private:
35  static const KKStr& MachineLearningHomeDir ();
36 
37  static KKStr machineLearningHomeDir;
38  }; /* KKMLVariables */
39 } /* KKMLL*/
40 #endif
static KKStr TrainingModelsDir()
static KKStr TempDir()
static void SetMachineLearninigHomeDir(const KKStr &_machineLearningHomeDir)
static KKStr Concat(const std::vector< std::string > &values)
Concatenates the list of &#39;std::string&#39; strings.
Definition: KKStr.cpp:1082
void EncodeProblem(const struct svm_paramater &param, struct svm_problem &prob_in, struct svm_problem &prob_out)
static KKStr TrainingLibrariesDir()