Here are the classes, structs, unions and interfaces with brief descriptions:
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  theplu | The Department of Theoretical Physics namespace as we define it |
  yat | Yat project namespace |
  classifier | Classifier related classes |
  BootstrapSampler | Class creating trainingset and validationset using bootstrapping |
| ConsensusInputRanker | Robust algorithm to rank rows in a data matrix versus a target vector |
| CrossValidationSampler | Class splitting a set into training set and validation set in a crossvalidation manner |
| DataLookup1D | Class for general vector view |
| DataLookupWeighted1D | Class for general weighted vector view |
| EnsembleBuilder | Class for ensembles of supervised classifiers |
| FeatureSelector | Interface class for FeatureSelection |
| FeatureSelectorIR | FeatureSelector using an InputRanker |
| FeatureSelectorRandom | Class for selection features by random |
| GaussianKernelFunction | Class for Gaussian kernel calculations |
| IGP | Class for In Group Proportions (IGP) |
| IRRank | Functor retrieving minus rank from a InputRanker to build a ConsensusInputRanker |
| IRRetrieve | Interface class for retrieving information from a InputRanker to build a ConsensusInputRanker |
| InputRanker | Class for ranking rows in a matrix, using a Score and a target vector |
| Kernel | Interface Class for Kernels |
| KernelFunction | Interface class calculating elements in Kernel |
| KernelLookup | Lookup into Kernel |
| Kernel_MEV | Memory Efficient Kernel |
| Kernel_SEV | Speed Efficient Kernel |
| KNN | Nearest Neighbor Classifier |
| NeighborWeightingConcept | Concept check for a Neighbor Weighting Method |
| 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 |
| 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 |
| 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 |
| MatrixLookup | General view into utility::Matrix |
| MatrixLookupWeighted | General view into utility::MatrixWeighted |
| NBC | Naive Bayesian Classifier |
| NCC | Nearest Centroid Classifier |
| PolynomialKernelFunction | Class for polynomial kernel calculations |
| SVM | Support Vector Machine |
| SvmMultiClass | Support Vector Machine for more than two classes |
| SVindex | |
| Sampler | Interface class for dividing samples into training and validation |
| SubsetGenerator | Class splitting Data into training and validation set |
| SupervisedClassifier | Interface class for supervised classifiers that use data in a matrix format |
 Target | Class for containing sample labels |
| normalizer | Normalization of data |
| detail | |
| Centralizer | Centralize a range |
| ColumnNormalizer | Using a functor T to normalize each column |
| Gauss | Gaussian Normalizer |
| qQuantileNormalizer | Perform Q-quantile normalization |
| QuantileNormalizer | Perform quantile normalization |
| RowNormalizer | Using a functor T to normalize each column |
| Spearman | Replace elements with normalized rank |
| Zscore | Zero mean and unity variance |
| omic | Classes and functions related to genomics and proteomics |
| BamFile | |
| InBamFile | |
| OutBamFile | |
| BamHeader | |
| BamRead | Class holding a bam query |
| BamLessPos | |
| BamLessEnd | |
| BamReadIterator | Class to iterate through a InBamFile |
| BamWriter | |
| BamWriteIterator | Output iterator for bam file |
| Codon | |
| AminoAcidEqual | Functor comparing if two Codons translate to the same amino acid |
| DNA | |
| GenomicPosition | |
| GFF | |
| GFF2 | |
| GFF3 | |
| random | Random number distributions |
| RNG | Random Number Generator |
| RNG_state | Class holding state of a random generator |
| Discrete | Discrete random number distributions |
| Binomial | Binomial distribution |
| DiscreteGeneral | General |
| DiscreteUniform | Discrete uniform distribution |
| Poisson | Poisson Distribution |
| Continuous | Continuous random number distributions |
| ContinuousUniform | Uniform distribution |
| ContinuousGeneral | Generates numbers from a histogram in a continuous manner |
| Exponential | Generator of random numbers from an exponential distribution |
| Gaussian | Gaussian distribution |
| regression | Statistical modeling of data |
| AkimaInterpolation | Non-rounded Akima spline with natural boundary conditions |
| AkimaPeriodicInterpolation | AkimaPeriodic interpolation |
| CSplineInterpolation | Cubic spline with natural boundary conditions |
| CSplinePeriodicInterpolation | Cubic spline with periodic boundary conditions |
| GSLInterpolation | Base class for interfacing GSL interpolation |
| Kernel | Interface Class for calculating the weights in a more general way than classical rectangular windows |
| KernelBox | Class for KernelBox a.k.a. rectangular window |
| KernelTriCube | Class for TriCubal kernel |
| Linear | Linear regression |
| LinearInterpolation | Linear interpolation |
| LinearWeighted | Linear regression |
| Local | Class for Locally weighted regression |
| MultiDimensional | MultiDimesional fitting |
| MultiDimensionalWeighted | MultiDimesional fitting |
| Naive | Naive Regression |
| NaiveWeighted | Naive fitting |
| OneDimensional | Interface Class for One Dimensional fitting |
| OneDimensionalWeighted | Interface Class for One Dimensional fitting in a weighted fashion |
| Polynomial | Polynomial regression |
| PolynomialInterpolation | Polynomial interpolation |
| PolynomialWeighted | Polynomial Regression in weighted fashion |
| TukeyBiweight | |
| statistics | Statistical methods, classes, and functions |
| AUC | Area Under ROC Curve |
| averager_base | Base class for averager classes |
| averager_base2 | Base class for averagers calculating mean and variance |
| averager_base3 | |
| averager_base4 | |
| Average | Functor to take average of a range |
| Averager | Class to calculate simple (first and second moments) averages |
| Averager1 | Class to calculate mean |
| Averager3 | Class to calculate 1st, 2nd, and 3rd central moments |
| Averager4 | Class to calculate 1st, 2nd, 3rd, and 4th central moments |
| AveragerPair | Class for taking care of mean and covariance of two variables |
| AveragerWeighted | Class to calulate averages with weights |
| AveragerPairWeighted | Class for taking care of mean and covariance of two variables in a weighted manner |
| averager_traits | |
| averager_traits< utility::unweighted_iterator_tag > | |
| averager_traits< utility::weighted_iterator_tag > | |
| averager | |
| averager_pair | |
| EuclideanDistance | Calculates the Euclidean distance between two points given by elements of ranges |
| Fisher | Fisher's exact test |
| FoldChange | Score given by the difference by the group means |
| Histogram | Histograms provide a convenient way of presenting the distribution of a set of data |
| Kendall | Kendall's tau rank coefficient |
| KolmogorovSmirnov | Kolmogorov Smirnov Test |
| Element | |
| Pearson | Class for calculating Pearson correlation |
| PearsonCorrelation | Class for calculating Pearson correlation |
| PearsonDistance | Calculates the Pearson correlation distance between two points given by elements of ranges |
| Percentiler | Functor to calculate percentile of a range |
| ROC | Reciever Operating Characteristic |
| SAMScore | Class for score used in Significance Analysis of Microarrays (SAM) |
| Score | Interface Class for score classes |
| Smoother | Estimating a distribution in a smooth fashion |
| SNRScore | Class for score based on signal-to-noise ratio (SNRScore) |
| Spearman | Spearman rank correlation coefficient |
| TukeyBiweightEstimator | Tukey's Biweight Estimator |
| tScore | Class for Fisher's t-test |
| tTest | Class for Student's t-test |
| VectorFunction | Interface Class for vector functors |
| Max | Larget element |
| Median | Median element |
| Mean | Mean element |
| Min | Smallest element |
| Nth_Element | |
| WilcoxonFoldChange | WilcoxonFoldChange |
 utility | Miscellaneous functionality |
| detail | |
| weighted_iterator_traits_detail | |
| weighted_iterator_traits_detail< T, typename boost::enable_if< typename boost::is_convertible< T, DataWeight > >::type > | |
| unweighted_type_and | |
| unweighted_type_and< unweighted_iterator_tag, unweighted_iterator_tag > | |
| iter_has_mutable_data | |
| iter_has_mutable_weight | |
| is_weighted | |
| is_unweighted | |
| iterator_traits_detail | |
| mutable_reference | |
| mutable_reference< true > | |
| iterator_traits_detail< Iter, typename boost::enable_if< is_weighted< Iter > >::type > | |
| VectorPusher | |
| VectorPusher< std::string > | |
| Aligner | Aligning two sequences |
| ColumnStream | |
| CommandLine | Class for parsing the command line |
| Container2D | Concept check for Container2D |
| Mutable_Container2D | Concept check for Mutable Container2D |
| TrivialIterator | Concept check for Trivial Iterator |
| DataIteratorConcept | Concept check for Data Iterator |
| DistanceConcept | Concept check for a Distance |
| Container2DIterator | Iterator for a Container2D |
| DataIterator | DataIterator |
| DataWeight | Holds a pair of data and associated weight |
| DataWeightProxy | Proxy class for DataWeight |
| Deleter | Functor that deletes an object |
| runtime_error | Class used for all runtime error detected within yat library |
| cmd_error | Class used for error reported from Commandline or Option |
| errno_error | Class that contains information reported via global variable errno |
| GSL_error | Class for errors reported from underlying GSL calls |
| IO_error | Class to report errors associated with IO operations |
| FileUtil | Checking file/directory existence and access permissions |
| GetlineIterator | Read from std::istream with std::getline |
| Index | Class for storing indices of, e.g., a MatrixLookup |
| unweighted_iterator_tag | |
| weighted_iterator_tag | |
| weighted_iterator_traits | |
| weighted_if_any2 | |
| weighted_if_any3 | |
| iterator_traits | |
| KernelPCA | Principal Component Analysis on a Kernel Matrix |
| kNNI | KNNimpute |
| Matrix | Interface to GSL matrix |
| MatrixWeighted | Weighted Matrix |
| NNI | Interface class for nearest neighbour imputation (NNI) algorithms |
| Option | Container of variables for an option |
| OptionArg | Option with argument |
| OptionFile | Class for file related options |
| OptionInFile | Class for file related options |
| OptionOutFile | Class for file related options |
| OptionHelp | Class for help option |
| OptionSwitch | Class for switch option |
| PCA | Principal Component Analysis |
| Segment | Class for a Segment or Interval |
| SegmentCompare | Functor using compare |
| SegmentMap | Map of Segments |
| SegmentSet | Set of Segments |
| SegmentTree | Base Class for SegmentSet and SegmentMap |
| SmartPtr | |
| BasicStreamRedirect | Redirect a stream to another stream |
| Range | A class for storing a shallow copy of a Range |
| abs | |
| Dereferencer | Adaptor between pointer and pointee interface |
| compose_f_gx_hy | |
| compose_f_gxy | |
| compose_f_gx | |
| Exp | |
| Identity | Identity functor that returns its argument |
| less_nan | Functor that behaves like std::less with the exception that it treates NaN as a number larger than infinity |
| less_nan< DataWeight > | Specialization for DataWeight |
| Log | |
| pair_value_compare | Functor comparing pairs using second |
| PairFirst | Functor that return std::pair.first |
| PairSecond | Functor that return std::pair.second |
| StrideIterator | Adaptor using a stride on underlying iterator |
| SVD | Singular Value Decomposition |
| TypeInfo | Wrapper class for storing std::type_info |
| Vector | This is the yat interface to GSL vector |
| VectorBase | This is the yat interface to GSL vector |
| VectorConstView | Read-only view |
| VectorMutable | This is the mutable interface to GSL vector |
| VectorView | This is the yat interface to gsl_vector_view |
| WeightedIterator | WeightedIterator |
| WeightIterator | WeightIterator |
| WeNNI | Weighted Nearest Neighbour Imputation |
| noncopyable |
