A wrapper class to store same predictor trained on random selected samples to return prediction dist. More...
#include <GibbsSampler.h>
Inheritance diagram for PredictorOrEmpty< T >:
Public Member Functions | |
| T | get_sample (vector< T > &x, mt19937 &gen) |
| retrieves random sample for feature based on all other features | |
 Public Member Functions inherited from SerializableObject | |
| virtual int | version () const |
| Relevant for serializations. | |
| virtual string | my_class_name () const |
| For better handling of serializations it is highly recommended that each SerializableObject inheriting class will implement the next method. | |
| virtual void | serialized_fields_name (vector< string > &field_names) const |
| The names of the serialized fields. | |
| virtual void * | new_polymorphic (string derived_name) |
| for polymorphic classes that want to be able to serialize/deserialize a pointer * to the derived class given its type one needs to implement this function to return a new to the derived class given its type (as in my_type) | |
| virtual void | pre_serialization () |
| virtual void | post_deserialization () |
| virtual size_t | get_size () |
| Gets bytes sizes for serializations. | |
| virtual size_t | serialize (unsigned char *blob) |
| Serialiazing object to blob memory. return number ob bytes wrote to memory. | |
| virtual size_t | deserialize (unsigned char *blob) |
| Deserialiazing blob to object. returns number of bytes read. | |
| size_t | serialize_vec (vector< unsigned char > &blob) |
| size_t | deserialize_vec (vector< unsigned char > &blob) |
| virtual size_t | serialize (vector< unsigned char > &blob) |
| virtual size_t | deserialize (vector< unsigned char > &blob) |
| virtual int | read_from_file (const string &fname) |
| read and deserialize model | |
| virtual int | write_to_file (const string &fname) |
| serialize model and write to file | |
| virtual int | read_from_file_unsafe (const string &fname) |
| read and deserialize model without checking version number - unsafe read | |
| int | init_from_string (string init_string) |
| Init from string. | |
| int | init_params_from_file (string init_file) |
| int | init_param_from_file (string file_str, string ¶m) |
| virtual int | init (map< string, string > &map) |
| Virtual to init object from parsed fields. | |
| int | update_from_string (const string &init_string) |
| virtual int | update (map< string, string > &map) |
| Virtual to update object from parsed fields. | |
| virtual string | object_json () const |
Data Fields | |
| int | input_size |
| vector< T > | sample_cohort |
| all data points of feature | |
| MedPredictor * | predictor |
| predictors for each feature and probability to see Y (logloss function) | |
| vector< Calibrator > | calibrators |
| calibrator for probability for each pred | |
| vector< float > | bin_vals |
| the value of feature for each pred | |
| vector< float > | cluster_centers |
| for kMeans centers | |
| vector< vector< float > > | clusters_y |
| for kMeans centers | |
Detailed Description
template<typename T>
class PredictorOrEmpty< T >
class PredictorOrEmpty< T >
A wrapper class to store same predictor trained on random selected samples to return prediction dist.
The documentation for this class was generated from the following files:
- Internal/MedStat/MedStat/GibbsSampler.h
- Internal/MedStat/MedStat/GibbsSampler.cpp
