Machine Learning Library
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Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level
1
2
3
]
api__DirectoryCategory
api__doGetCachedPage
api__doGetCachedPageResponse
api__doGoogleSearch
api__doGoogleSearchResponse
api__doSpellingSuggestion
api__doSpellingSuggestionResponse
api__GoogleSearchResult
api__ResultElement
CArchiv
Base class of object serialization
CDatabaseException
CMysqlDatabaseException
CFlowItem
CMysqlDatabase
CObject< Type >
Base class for all object
CClusterAlgorithm< Type >
Base class for cluster algorithms
CSOM< Type >
SOM class for Self Organizing Maps with arbitrary topology
CDataset< Type >
Manages pairs of input and output vectors
CDatasetItem< Type >
Single item of a dataset consisting of a pair of input and out vectors
CDatasetStatistic< Type >
CKernel< Type >
Base class for kernel functions Base class for kernel function used for example by the support vector machine
CAnovaKernel< Type >
ANOVA kernel function
CChiSquaredKernel< Type >
CDoubleExponentialKernel< Type >
Double-Exponential kernel function
CEpanechnikovKernel< Type >
CGaussianKernel< Type >
Gaussian kernel function
CLinearKernel< Type >
Linear kernel function
CMultiVariateGaussianKernel< Type >
CPlummerKernel< Type >
Plummer kernel function
CPolynomialKernel< Type >
Polynomial kernel function
CTriangularKernel< Type >
Triangular kernel function
CLearnRate< Type >
Base class for all learning rate functions Template base class for all learning rates (virtual)
CConstantRate< Type >
Constante learn rate Template class for constant learn rates
CExponentialRate< Type >
Exponential decreasing learn rate Template class for exponential decreasing learning rates. The learning rate is defined as initial*(final/initial)^(t/tmax).)
CHarmonicRate< Type >
CLinearRate< Type >
Linear decreasing learn rate Template class for linear decreasing learning rates
CMatrix< Type >
Template object implementing a matrix of single and double precision elements
CMetric< Type >
Base class for metrix objects
CAngleMetric< Type >
Angle based metric object
CCoCosineMetric< Type >
CoCosine metric object Template class for metric based on scalar product
CEuclideanMetric< Type >
Euclidean metric object
CEuclideanMetric2< Type >
Euclidean2 metric object
CHyperbolicMetric< Type >
Hyperbolic metric object
CManhattenMetric< Type >
Manhatten metric object
CMaximumMetric< Type >
Maximum metric object
CScalarMetric< Type >
Scalar metric object Template class for metric based on scalar product
COptimizer< Type >
Base class for optimisation techniques; ..
CProjection< Type >
Base class for projection algorithms like PCA, ICA, KPCA, etc
CVector< Type >
Templatized vector for numerical applications
CDenseVector< Type >
Template object for vectors of single and double precision and integer
CDenseVector< double >
CSparseVector< Type >
Sparse, immutable vector representation
CVector< T >
CDenseVector< T >
CObject< double >
CDataset< double >
CMetric< double >
CObject< float >
CDataset< float >
CObjectFactory
Produces objects of given name and type
CSomTopology< Type >
CCartesianTopology< Type >
Topology class for n dimensional cartesian grid
CHyperbolicTopology< Type >
Topology class describing two dimensional hyperbolic lattice structure
CVectorOperations< T >
CVectorOperations< Type >
DirectoryCategoryArray
euclidean_norm< Type >
ios
gzstreambase
igzstream
ogzstream
istream
igzstream
std::iterator_traits< const keyed_iterator< Type > >
std::iterator_traits< keyed_iterator< Type > >
keyed_iterator< Type >
mvGenerator
Namespace
ostream
ogzstream
random_access_iterator_tag
keyed_iterator_tag
RandomNumber
ResultElementArray
soap
googleapi
soap_array
soap_attribute
soap_blist
soap_clist
soap_code_map
soap_cookie
soap_dime
soap_dom_attribute
soap_dom_element
soap_double_nan
SOAP_ENV__Code
SOAP_ENV__Detail
SOAP_ENV__Fault
SOAP_ENV__Header
soap_flist
soap_ilist
soap_mime
soap_multipart
soap_nlist
soap_plist
soap_plugin
streambuf
gzstreambuf
strEqual
xsd__base64Binary
exception
CException
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