Classes | |
class | BootstrapSampler |
Class creating trainingset and validationset using bootstrapping. More... | |
class | ConsensusInputRanker |
Robust algorithm to rank rows in a data matrix versus a target vector. More... | |
class | CrossValidationSampler |
Class splitting a set into training set and validation set in a crossvalidation manner. More... | |
class | DataLookup1D |
Class for general vector view. More... | |
class | DataLookupWeighted1D |
Class for general weighted vector view. More... | |
class | EnsembleBuilder |
Class for ensembles of supervised classifiers. More... | |
class | FeatureSelector |
Interface class for FeatureSelection. More... | |
class | FeatureSelectorIR |
FeatureSelector using an InputRanker. More... | |
class | FeatureSelectorRandom |
Class for selection features by random. More... | |
class | GaussianKernelFunction |
Class for Gaussian kernel calculations. More... | |
class | IGP |
Class for In Group Proportions (IGP) See Kapp and Tibshirani, Biostatistics (2006). More... | |
class | InputRanker |
Class for ranking rows in a matrix, using a Score and a target vector. More... | |
class | IRRank |
Functor retrieving minus rank from a InputRanker to build a ConsensusInputRanker. More... | |
class | IRRetrieve |
Interface class for retrieving information from a InputRanker to build a ConsensusInputRanker. More... | |
class | Kernel |
Interface Class for Kernels. More... | |
class | Kernel_MEV |
Memory Efficient Kernel. More... | |
class | Kernel_SEV |
Speed Efficient Kernel. More... | |
class | KernelFunction |
Interface class calculating elements in Kernel. More... | |
class | KernelLookup |
Lookup into Kernel. More... | |
class | KNN |
Nearest Neighbor Classifier. More... | |
struct | KNN_ReciprocalDistance |
A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample. More... | |
struct | KNN_ReciprocalRank |
A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample. More... | |
struct | KNN_Uniform |
A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample. More... | |
class | MatrixLookup |
General view into utility::Matrix. More... | |
class | MatrixLookupWeighted |
General view into utility::MatrixWeighted. More... | |
class | NBC |
Naive Bayesian Classifier. More... | |
class | NCC |
Nearest Centroid Classifier. More... | |
class | PolynomialKernelFunction |
Class for polynomial kernel calculations. More... | |
class | Sampler |
Interface class for dividing samples into training and validation. More... | |
class | SubsetGenerator |
Class splitting Data into training and validation set. More... | |
class | SupervisedClassifier |
Interface class for supervised classifiers that use data in a matrix format. More... | |
class | SVindex |
class | SVM |
Support Vector Machine. More... | |
class | Target |
Class for containing sample labels. More... | |
Functions | |
std::ostream & | operator<< (std::ostream &s, const DataLookup1D &v) |
The output operator for DataLookup1D. | |
double | sum_weight (const DataLookupWeighted1D &) |
std::ostream & | operator<< (std::ostream &s, const MatrixLookup &) |
std::ostream & | operator<< (std::ostream &s, const MatrixLookupWeighted &) |
std::ostream & | operator<< (std::ostream &, const Target &) |
void | convert (const DataLookup1D &, utility::Vector &) |
void | convert (const DataLookupWeighted1D &, utility::Vector &value, utility::Vector &weight) |
All classes associated with usage of classifiers are defined within this namespace.
void theplu::yat::classifier::convert | ( | const DataLookupWeighted1D & | , | |
utility::Vector & | value, | |||
utility::Vector & | weight | |||
) |
Converts a DataLookupWeighted1D to two utility::vector
void theplu::yat::classifier::convert | ( | const DataLookup1D & | , | |
utility::Vector & | ||||
) |
Converts a DataLookup1D to a utility::vector
std::ostream& theplu::yat::classifier::operator<< | ( | std::ostream & | , | |
const Target & | ||||
) |
The output operator for the Target class.
std::ostream& theplu::yat::classifier::operator<< | ( | std::ostream & | s, | |
const MatrixLookupWeighted & | ||||
) |
The output operator MatrixLookupWeighted
For eacd data element data(i,j) is printed except those being associated with a zero weight for which nothing is printed.
std::ostream& theplu::yat::classifier::operator<< | ( | std::ostream & | s, | |
const MatrixLookup & | ||||
) |
The output operator MatrixLookup
std::ostream& theplu::yat::classifier::operator<< | ( | std::ostream & | s, | |
const DataLookup1D & | v | |||
) |
The output operator for DataLookup1D.
Elements are separated by the character from the omanip fill. The following example will write the elements separated by tab.
char prev=s.fill('\t'); s << v; s.fill(prev);
double theplu::yat::classifier::sum_weight | ( | const DataLookupWeighted1D & | ) |