Public Member Functions | Protected Member Functions | Protected Attributes

CTOPFeatures Class Reference

Detailed Description

The class TOPFeatures implements TOP kernel features obtained from two Hidden Markov models.

It was used in

K. Tsuda, M. Kawanabe, G. Raetsch, S. Sonnenburg, and K.R. Mueller. A new discriminative kernel from probabilistic models. Neural Computation, 14:2397-2414, 2002.

which also has the details.

Note that TOP-features are computed on the fly, so to be effective feature caching should be enabled.

It inherits its functionality from CSimpleFeatures, which should be consulted for further reference.

Definition at line 68 of file TOPFeatures.h.

Inheritance diagram for CTOPFeatures:
Inheritance graph

List of all members.

Public Member Functions

 CTOPFeatures ()
 CTOPFeatures (int32_t size, CHMM *p, CHMM *n, bool neglin, bool poslin)
 CTOPFeatures (const CTOPFeatures &orig)
virtual ~CTOPFeatures ()
void set_models (CHMM *p, CHMM *n)
virtual float64_tset_feature_matrix ()
int32_t compute_num_features ()
bool compute_relevant_indizes (CHMM *hmm, T_HMM_INDIZES *hmm_idx)
virtual const char * get_name () const

Protected Member Functions

virtual float64_tcompute_feature_vector (int32_t num, int32_t &len, float64_t *target=NULL)
void compute_feature_vector (float64_t *addr, int32_t num, int32_t &len)

Protected Attributes

bool neglinear
bool poslinear
T_HMM_INDIZES pos_relevant_indizes
T_HMM_INDIZES neg_relevant_indizes

Constructor & Destructor Documentation

CTOPFeatures (  ) 

default constructor

Definition at line 18 of file TOPFeatures.cpp.

CTOPFeatures ( int32_t  size,
bool  neglin,
bool  poslin 


size cache size
p positive HMM
n negative HMM
neglin if negative HMM is of linear shape
poslin if positive HMM is of linear shape

Definition at line 23 of file TOPFeatures.cpp.

CTOPFeatures ( const CTOPFeatures orig  ) 

copy constructor

Definition at line 34 of file TOPFeatures.cpp.

~CTOPFeatures (  )  [virtual]

Definition at line 44 of file TOPFeatures.cpp.

Member Function Documentation

float64_t * compute_feature_vector ( int32_t  num,
int32_t &  len,
float64_t target = NULL 
) [protected, virtual]

compute feature vector

num num
len len
something floaty

Reimplemented from CSimpleFeatures< float64_t >.

Definition at line 88 of file TOPFeatures.cpp.

void compute_feature_vector ( float64_t addr,
int32_t  num,
int32_t &  len 
) [protected]

computes the feature vector to the address addr

addr address
num num
len len

Definition at line 104 of file TOPFeatures.cpp.

int32_t compute_num_features (  ) 

compute number of features

number of features

Definition at line 335 of file TOPFeatures.cpp.

bool compute_relevant_indizes ( CHMM hmm,
T_HMM_INDIZES *  hmm_idx 

compute relevant indices

hmm HMM to compute for
hmm_idx HMM index
if computing was successful

Definition at line 232 of file TOPFeatures.cpp.

virtual const char* get_name ( void   )  const [virtual]
object name

Reimplemented from CSimpleFeatures< float64_t >.

Definition at line 117 of file TOPFeatures.h.

float64_t * set_feature_matrix (  )  [virtual]

set feature matrix

something floaty

Definition at line 193 of file TOPFeatures.cpp.

void set_models ( CHMM p,

set HMMs

p positive HMM
n negative HMM

Definition at line 64 of file TOPFeatures.cpp.

Member Data Documentation

CHMM* neg [protected]

negative HMM

Definition at line 145 of file TOPFeatures.h.

T_HMM_INDIZES neg_relevant_indizes [protected]

negative relevant indices

Definition at line 154 of file TOPFeatures.h.

bool neglinear [protected]

if negative HMM is a LinearHMM

Definition at line 147 of file TOPFeatures.h.

CHMM* pos [protected]

positive HMM

Definition at line 143 of file TOPFeatures.h.

T_HMM_INDIZES pos_relevant_indizes [protected]

positive relevant indices

Definition at line 152 of file TOPFeatures.h.

bool poslinear [protected]

if positive HMM is a LinearHMM

Definition at line 149 of file TOPFeatures.h.

The documentation for this class was generated from the following files:
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