, including all inherited members.
  | _classname_() | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _getOptionList_() | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _getRemoteMethodMap_() | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _isa_(const Object *o) | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _new_instance_for_typemap_() | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _static_initialize_() | PLearn::AdditiveNormalizationKernel |  [static] | 
  | _static_initializer_ | PLearn::AdditiveNormalizationKernel |  [static] | 
  | addDataForKernelMatrix(const Vec &newRow) | PLearn::SourceKernel |  [virtual] | 
  | AdditiveNormalizationKernel() | PLearn::AdditiveNormalizationKernel |  | 
  | AdditiveNormalizationKernel(Ker the_source, bool remove_bias=false, bool remove_bias_in_evaluate=false, bool double_centering=false) | PLearn::AdditiveNormalizationKernel |  | 
  | all_k_x | PLearn::AdditiveNormalizationKernel |  [mutable, private] | 
  | apply(VMat m1, VMat m2, Mat &result) const  | PLearn::Kernel |  | 
  | apply(VMat m1, VMat m2) const  | PLearn::Kernel |  | 
  | apply(VMat m, const Vec &x, Vec &result) const  | PLearn::Kernel |  | 
  | apply(Vec x, VMat m, Vec &result) const  | PLearn::Kernel |  | 
  | asString() const  | PLearn::Object |  [virtual] | 
  | asStringRemoteTransmit() const  | PLearn::Object |  [virtual] | 
  | average_col | PLearn::AdditiveNormalizationKernel |  [protected] | 
  | average_row | PLearn::AdditiveNormalizationKernel |  [protected] | 
  | avg_evaluate_i_x_again | PLearn::AdditiveNormalizationKernel |  [mutable, protected] | 
  | avg_evaluate_x_i_again | PLearn::AdditiveNormalizationKernel |  [mutable, protected] | 
  | build() | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | build_() | PLearn::AdditiveNormalizationKernel |  [private] | 
  | cache_gram_matrix | PLearn::Kernel |  | 
  | call(const string &methodname, int nargs, PStream &io) | PLearn::Object |  [virtual] | 
  | changeOption(const string &optionname, const string &value) | PLearn::Object |  | 
  | changeOptions(const map< string, string > &name_value) | PLearn::Object |  [virtual] | 
  | classname() const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | computeAverage(const Vec &x, bool on_row, real squared_norm_of_x=-1) const  | PLearn::AdditiveNormalizationKernel |  [inline, protected] | 
  | computeGramMatrix(Mat K) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | computeGramMatrixDerivative(Mat &KD, const string &kernel_param, real epsilon=1e-6) const  | PLearn::Kernel |  [virtual] | 
  | computeKNNeighbourMatrixFromDistanceMatrix(const Mat &D, int knn, bool insure_self_first_neighbour=true, bool report_progress=false) | PLearn::Kernel |  [static] | 
  | computeNearestNeighbors(const Vec &x, Mat &k_xi_x_sorted, int knn) const  | PLearn::Kernel |  | 
  | computeNeighbourMatrixFromDistanceMatrix(const Mat &D, bool insure_self_first_neighbour=true, bool report_progress=false) | PLearn::Kernel |  [static] | 
  | computePartialGramMatrix(const TVec< int > &subset_indices, Mat K) const  | PLearn::Kernel |  [virtual] | 
  | computeSparseGramMatrix(TVec< Mat > K) const  | PLearn::Kernel |  [virtual] | 
  | computeTestGramMatrix(Mat test_elements, Mat K, Vec self_cov) const  | PLearn::Kernel |  [virtual] | 
  | data | PLearn::Kernel |  [protected] | 
  | data_inputsize | PLearn::Kernel |  [protected] | 
  | data_will_change | PLearn::AdditiveNormalizationKernel |  | 
  | dataInputsize() const  | PLearn::Kernel |  [inline] | 
  | declareMethods(RemoteMethodMap &rmm) | PLearn::Kernel |  [protected, static] | 
  | declareOptions(OptionList &ol) | PLearn::AdditiveNormalizationKernel |  [protected, static] | 
  | declaringFile() | PLearn::AdditiveNormalizationKernel |  [inline, static] | 
  | deepCopy(CopiesMap &copies) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | deepCopyNoMap() | PLearn::Object |  | 
  | double_centering | PLearn::AdditiveNormalizationKernel |  | 
  | estimateHistograms(VMat d, real sameness_threshold, real minval, real maxval, int nbins) const  | PLearn::Kernel |  | 
  | estimateHistograms(Mat input_and_class, real minval, real maxval, int nbins) const  | PLearn::Kernel |  | 
  | evaluate(const Vec &x1, const Vec &x2) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | evaluate_all_i_x(const Vec &x, const Vec &k_xi_x, real squared_norm_of_x=-1, int istart=0) const  | PLearn::Kernel |  [virtual] | 
  | evaluate_all_x_i(const Vec &x, const Vec &k_x_xi, real squared_norm_of_x=-1, int istart=0) const  | PLearn::Kernel |  [virtual] | 
  | evaluate_i_j(int i, int j) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | evaluate_i_x(int i, const Vec &x, real squared_norm_of_x=-1) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | evaluate_i_x_again(int i, const Vec &x, real squared_norm_of_x=-1, bool first_time=false) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | evaluate_x_i(const Vec &x, int i, real squared_norm_of_x=-1) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | evaluate_x_i_again(const Vec &x, int i, real squared_norm_of_x=-1, bool first_time=false) const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | factor | PLearn::AdditiveNormalizationKernel |  [protected] | 
  | getData() | PLearn::Kernel |  [inline] | 
  | getOption(const string &optionname) const  | PLearn::Object |  | 
  | getOptionList() const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | getOptionMap() const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | getOptionsToRemoteTransmit() const  | PLearn::Object |  [virtual] | 
  | getOptionsToSave() const  | PLearn::Object |  [virtual] | 
  | getParameters() const  | PLearn::SourceKernel |  [virtual] | 
  | getRemoteMethodMap() const  | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | gram_matrix | PLearn::Kernel |  [mutable, protected] | 
  | gram_matrix_is_cached | PLearn::Kernel |  [mutable, protected] | 
  | hasData() | PLearn::Kernel |  | 
  | hasOption(const string &optionname) const  | PLearn::Object |  | 
  | info() const  | PLearn::Object |  [virtual] | 
  | inherited typedef | PLearn::AdditiveNormalizationKernel |  [private] | 
  | is_symmetric | PLearn::Kernel |  | 
  | isInData(const Vec &x, int *i=0) const  | PLearn::Kernel |  | 
  | Kernel(bool is__symmetric=true, bool call_build_=false) | PLearn::Kernel |  | 
  | load(const PPath &filename) | PLearn::Object |  [virtual] | 
  | makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | n_examples | PLearn::Kernel |  [protected] | 
  | newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object |  | 
  | newwrite(PStream &out) const  | PLearn::Object |  [virtual] | 
  | nExamples() const  | PLearn::Kernel |  [inline] | 
  | Object(bool call_build_=false) | PLearn::Object |  | 
  | oldread(istream &in) | PLearn::Object |  [virtual] | 
  | operator()(const Vec &x1, const Vec &x2) const  | PLearn::Kernel |  [inline] | 
  | parseOptionName(const string &optionname, Object *&final_object, OptionList::iterator &option_iter, string &option_index) | PLearn::Object |  | 
  | parseOptionName(const string &optionname, const Object *&final_object, OptionList::iterator &option_iter, string &option_index) const  | PLearn::Object |  | 
  | PPointable() | PLearn::PPointable |  [inline] | 
  | PPointable(const PPointable &other) | PLearn::PPointable |  [inline] | 
  | prepareToSendResults(PStream &out, int nres) | PLearn::Object |  [static] | 
  | read(istream &in) | PLearn::Object |  [virtual] | 
  | readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX) | PLearn::Object |  | 
  | ref() const  | PLearn::PPointable |  [inline] | 
  | remove_bias | PLearn::AdditiveNormalizationKernel |  | 
  | remove_bias_in_evaluate | PLearn::AdditiveNormalizationKernel |  | 
  | report_progress | PLearn::Kernel |  | 
  | returnComputedGramMatrix() const  | PLearn::Kernel |  [virtual] | 
  | run() | PLearn::Object |  [virtual] | 
  | save(const PPath &filename) const  | PLearn::Object |  [virtual] | 
  | setDataForKernelMatrix(VMat the_data) | PLearn::AdditiveNormalizationKernel |  [virtual] | 
  | setOption(const string &optionname, const string &value) | PLearn::Object |  | 
  | setParameters(Vec paramvec) | PLearn::SourceKernel |  [virtual] | 
  | source_kernel | PLearn::SourceKernel |  | 
  | SourceKernel() | PLearn::SourceKernel |  | 
  | sparse_gram_matrix | PLearn::Kernel |  [mutable, protected] | 
  | sparse_gram_matrix_is_cached | PLearn::Kernel |  [mutable, protected] | 
  | specify_dataset | PLearn::Kernel |  | 
  | test(VMat d, real threshold, real sameness_below_threshold, real sameness_above_threshold) const  | PLearn::Kernel |  | 
  | total_average | PLearn::AdditiveNormalizationKernel |  [protected] | 
  | total_average_unbiased | PLearn::AdditiveNormalizationKernel |  [protected] | 
  | train(VMat data) | PLearn::Kernel |  [virtual] | 
  | unref() const  | PLearn::PPointable |  [inline] | 
  | usage() const  | PLearn::PPointable |  [inline] | 
  | write(ostream &out) const  | PLearn::Object |  [virtual] | 
  | writeOptionVal(PStream &out, const string &optionname) const  | PLearn::Object |  | 
  | ~Kernel() | PLearn::Kernel |  [virtual] | 
  | ~Object() | PLearn::Object |  [virtual] | 
  | ~PPointable() | PLearn::PPointable |  [inline, virtual] |