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Machine.h File Reference

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Classes

class  CMachine
 A generic learning machine interface. More...

Macros

#define MACHINE_PROBLEM_TYPE(PT)

Enumerations

enum  EMachineType {
  CT_NONE = 0, CT_LIGHT = 10, CT_LIGHTONECLASS = 11, CT_LIBSVM = 20,
  CT_LIBSVMONECLASS = 30, CT_LIBSVMMULTICLASS = 40, CT_MPD = 50, CT_GPBT = 60,
  CT_CPLEXSVM = 70, CT_PERCEPTRON = 80, CT_KERNELPERCEPTRON = 90, CT_LDA = 100,
  CT_LPM = 110, CT_LPBOOST = 120, CT_KNN = 130, CT_SVMLIN = 140,
  CT_KERNELRIDGEREGRESSION = 150, CT_GNPPSVM = 160, CT_GMNPSVM = 170, CT_SVMPERF = 200,
  CT_LIBSVR = 210, CT_SVRLIGHT = 220, CT_LIBLINEAR = 230, CT_KMEANS = 240,
  CT_HIERARCHICAL = 250, CT_SVMOCAS = 260, CT_WDSVMOCAS = 270, CT_SVMSGD = 280,
  CT_MKLMULTICLASS = 290, CT_MKLCLASSIFICATION = 300, CT_MKLONECLASS = 310, CT_MKLREGRESSION = 320,
  CT_SCATTERSVM = 330, CT_DASVM = 340, CT_LARANK = 350, CT_DASVMLINEAR = 360,
  CT_GAUSSIANNAIVEBAYES = 370, CT_AVERAGEDPERCEPTRON = 380, CT_SGDQN = 390, CT_CONJUGATEINDEX = 400,
  CT_LINEARRIDGEREGRESSION = 410, CT_LEASTSQUARESREGRESSION = 420, CT_QDA = 430, CT_NEWTONSVM = 440,
  CT_GAUSSIANPROCESSREGRESSION = 450, CT_LARS = 460, CT_MULTICLASS = 470, CT_DIRECTORLINEAR = 480,
  CT_DIRECTORKERNEL = 490, CT_LIBQPSOSVM = 500, CT_PRIMALMOSEKSOSVM = 510, CT_CCSOSVM = 520,
  CT_GAUSSIANPROCESSBINARY = 530, CT_GAUSSIANPROCESSMULTICLASS = 540, CT_STOCHASTICSOSVM = 550, CT_NEURALNETWORK = 560,
  CT_BAGGING = 570, CT_FWSOSVM = 580, CT_BCFWSOSVM = 590, CT_GAUSSIANPROCESSCLASS
}
enum  ESolverType {
  ST_AUTO = 0, ST_CPLEX = 1, ST_GLPK = 2, ST_NEWTON = 3,
  ST_DIRECT = 4, ST_ELASTICNET = 5, ST_BLOCK_NORM = 6
}
enum  EProblemType {
  PT_BINARY = 0, PT_REGRESSION = 1, PT_MULTICLASS = 2, PT_STRUCTURED = 3,
  PT_LATENT = 4, PT_CLASS = 5
}

Macro Definition Documentation

#define MACHINE_PROBLEM_TYPE (   PT)
Value:
\
virtual EProblemType get_machine_problem_type() const { return PT; }

Definition at line 120 of file Machine.h.


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