00001 // This is mul/clsfy/clsfy_random_forest.h 00002 #ifndef clsfy_random_forest_h_ 00003 #define clsfy_random_forest_h_ 00004 //: 00005 // \file 00006 // \brief Binary tree classifier 00007 // \author Martin Roberts 00008 #include <clsfy/clsfy_classifier_base.h> 00009 #include <clsfy/clsfy_binary_tree.h> 00010 #include <mbl/mbl_cloneable_ptr.h> 00011 #include <vcl_iosfwd.h> 00012 00013 00014 //: Forest of clsfy_binary_tree trees 00015 // Note as it uses clsfy_binary_tree this is a 2-state (binary) classifier also 00016 class clsfy_random_forest : public clsfy_classifier_base 00017 { 00018 public: 00019 00020 //: Constructor 00021 00022 clsfy_random_forest(); 00023 00024 virtual ~clsfy_random_forest(); 00025 00026 00027 //: Return the classification of the given probe vector. 00028 virtual unsigned classify(const vnl_vector<double> &input) const; 00029 00030 //: Provides a probability-like value that the input being in each class. 00031 // output(i) i<nClasses, contains the probability that the input is in class i 00032 virtual void class_probabilities(vcl_vector<double> &outputs, const vnl_vector<double> &input) const; 00033 00034 //: This value has properties of a Log likelihood of being in class (binary classifiers only) 00035 // class probability = exp(logL) / (1+exp(logL)) 00036 virtual double log_l(const vnl_vector<double> &input) const; 00037 00038 //: The number of possible output classes. 00039 virtual unsigned n_classes() const {return 1;} 00040 00041 //: The dimensionality of input vectors. 00042 virtual unsigned n_dims() const; 00043 00044 //: Storage version number 00045 virtual short version_no() const; 00046 00047 //: Name of the class 00048 virtual vcl_string is_a() const; 00049 00050 //: Name of the class 00051 virtual bool is_class(vcl_string const& s) const; 00052 00053 //: Create a copy on the heap and return base class pointer 00054 virtual clsfy_classifier_base* clone() const; 00055 00056 //: Print class to os 00057 virtual void print_summary(vcl_ostream& os) const; 00058 00059 //: Save class to binary file stream 00060 virtual void b_write(vsl_b_ostream& bfs) const; 00061 00062 //: Load class from binary file stream 00063 virtual void b_read(vsl_b_istream& bfs); 00064 00065 unsigned ntrees() const {return trees_.size();} 00066 00067 void prune(); 00068 00069 //Append the tres of forest2 onto this 00070 clsfy_random_forest& operator+=(const clsfy_random_forest& forest2); 00071 00072 //: Merge the sub-forests in the input filenames into a single larger one 00073 friend void merge_sub_forests(const vcl_vector<vcl_string>& filenames, 00074 clsfy_random_forest& large_forest); 00075 //: Merge the sub-forests pointed to the input vector a single larger one 00076 friend void merge_sub_forests(const vcl_vector< clsfy_random_forest*>& sub_forests, 00077 clsfy_random_forest& large_forest); 00078 00079 //: Merge the two input forests 00080 friend clsfy_random_forest operator+(const clsfy_random_forest& forest1, 00081 const clsfy_random_forest& forest2); 00082 00083 00084 //: Provides a probability-like value that the input being in each class. 00085 // output(i) i<nClasses, contains the probability that the input is in class i 00086 // Do Out of bag estimates, i.e. only use trees whose vector of indices does not include this_indexs 00087 virtual void class_probabilities_oob(vcl_vector<double> &outputs, 00088 const vnl_vector<double> &input, 00089 const vcl_vector<vcl_vector<unsigned > >& oobIndices, 00090 unsigned this_index) const; 00091 00092 00093 //: Return the classification of the given probe vector using out of bag trees only. 00094 //See also class_probabilities_oob 00095 virtual unsigned classify_oob(const vnl_vector<double> &input, 00096 const vcl_vector<vcl_vector<unsigned > >& oobIndices, 00097 unsigned this_index) const; 00098 00099 private: 00100 00101 //: The trees in this forest 00102 vcl_vector<mbl_cloneable_ptr<clsfy_classifier_base> > trees_; 00103 00104 friend class clsfy_random_forest_builder; 00105 }; 00106 00107 #endif // clsfy_random_forest_h_
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