BayesClassifierMachine is the machine used by the BayesClassifier trainer to perform a Bayes Classification using different distributions.
Inheritance:
Public Fields
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int n_trainers
- the number of classes corresponds to the number of Trainer
-
Trainer** trainers
- the actual trainers
-
real* log_priors
- the log_prior probabilities of each class.
-
real* log_posteriors
- contains the log posterior probability plus the log prior of the class
-
bool allocated_log_priors
- used to know if log_priors where given or allocated
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ClassFormat* class_format
- the format of the data
-
List** trainers_measurers
- the measurers for each individual trainer
Public Methods
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BayesClassifierMachine( Trainer**, int n_trainers_, List** trainers_measurers_, ClassFormat* class_format_, real* log_priors_=NULL)
- creates a machine for BayesClassifier trainers, given a vector of trainers (one per class), an associate measurer for each trainer, a class_format that explains how the classes are coded, and an eventual vector (of size n_trainers_) containing the log of the class priors
-
virtual void forward( List* inputs )
- definition of virtual functions of Machine
Inherited from Machine:
Public Fields
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int n_inputs
-
int n_outputs
-
List* outputs
Public Methods
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virtual void reset()
Inherited from Object:
Public Methods
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virtual void init()
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void addOption(const char* name, int size, void* ptr, const char* help="", bool is_allowed_after_init=false)
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void addIOption(const char* name, int* ptr, int init_value, const char* help="", bool is_allowed_after_init=false)
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void addROption(const char* name, real* ptr, real init_value, const char* help="", bool is_allowed_after_init=false)
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void addBOption(const char* name, bool* ptr, bool init_value, const char* help="", bool is_allowed_after_init=false)
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void setOption(const char* name, void* ptr)
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void setIOption(const char* name, int option)
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void setROption(const char* name, real option)
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void setBOption(const char* name, bool option)
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virtual void loadFILE(FILE* file)
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virtual void saveFILE(FILE* file)
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void load(const char* filename)
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void save(const char* filename)
Documentation
BayesClassifierMachine is the machine used by the BayesClassifier
trainer to perform a Bayes Classification using different distributions.
The output corresponds to the class that is the most probable
(using prior AND posterior information).
int n_trainers
- the number of classes corresponds to the number of Trainer
Trainer** trainers
- the actual trainers
real* log_priors
- the log_prior probabilities of each class. default: log_priors are
taken as the log of the proportions in the training set.
real* log_posteriors
- contains the log posterior probability plus the log prior of the class
bool allocated_log_priors
- used to know if log_priors where given or allocated
ClassFormat* class_format
- the format of the data
List** trainers_measurers
- the measurers for each individual trainer
BayesClassifierMachine( Trainer**, int n_trainers_, List** trainers_measurers_, ClassFormat* class_format_, real* log_priors_=NULL)
- creates a machine for BayesClassifier trainers, given a vector of
trainers (one per class), an associate measurer for each trainer,
a class_format that explains how the classes are coded, and an eventual
vector (of size n_trainers_) containing the log of the class priors
virtual void forward( List* inputs )
- definition of virtual functions of Machine
- This class has no child classes.
- Author:
- Samy Bengio (bengio@idiap.ch)
Bison Ravi (francois.belisle@idiap.ch)
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