Memory Efficient Kernel.
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#include <yat/classifier/Kernel_MEV.h>
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| Kernel_MEV (const MatrixLookup &data, const KernelFunction &kf, const bool own=false) |
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| Kernel_MEV (const MatrixLookupWeighted &data, const KernelFunction &kf, const bool own=false) |
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| Kernel_MEV (const Kernel_MEV &kernel, const std::vector< size_t > &index) |
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double | operator() (const size_t row, const size_t column) const |
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const Kernel_MEV * | make_kernel (const MatrixLookup &, const bool own=false) const |
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const Kernel_MEV * | make_kernel (const MatrixLookupWeighted &, const bool own=false) const |
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const MatrixLookup & | data (void) const |
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const MatrixLookupWeighted & | data_weighted (void) const |
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double | element (const DataLookup1D &vec, const size_t i) const |
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double | element (const DataLookupWeighted1D &vec, const size_t i) const |
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size_t | size (void) const |
| number of samples
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bool | weighted (void) const |
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Memory Efficient Kernel.
Class taking care of the kernel matrix, where is number of samples. Type of Kernel is defined by a KernelFunction. This Memory Efficient Version (MEV) does not store the kernel matrix in memory, but calculates an element when it is needed. When memory allows do always use Kernel_SEV instead.
Constructor taking the data matrix and KernelFunction as input. Each column in the data matrix corresponds to one sample.
- Note
- Can not handle NaNs.
Constructor taking the data matrix and KernelFunction as input. Each column in the data matrix corresponds to one sample.
- Note
- Can not handle NaNs.
theplu::yat::classifier::Kernel_MEV::Kernel_MEV |
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const Kernel_MEV & |
kernel, |
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const std::vector< size_t > & |
index |
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) |
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Constructing a new Kernel based on selected features index. All other seeting are the same.
const MatrixLookup& theplu::yat::classifier::Kernel::data |
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void |
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const |
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inherited |
- Returns
- const reference to the underlying data.
- Exceptions
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- Returns
- const reference to the underlying data.
- Exceptions
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double theplu::yat::classifier::Kernel::element |
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const DataLookup1D & |
vec, |
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const size_t |
i |
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inherited |
Calculates the scalar product (using the KernelFunction) between vector vec and the th column in the data matrix.
double theplu::yat::classifier::Kernel::element |
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const DataLookupWeighted1D & |
vec, |
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const size_t |
i |
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inherited |
Calculates the weighted scalar product (using the KernelFunction) between vector vec and the th column in the data matrix. Using a weight vector with all elements equal to unity yields same result as the non-weighted version above.
const Kernel_MEV* theplu::yat::classifier::Kernel_MEV::make_kernel |
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const MatrixLookup & |
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const bool |
own = false |
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virtual |
An interface for making new classifier objects. This function allows for specification at run-time of which kernel to instatiate (see 'Prototype' in Design Patterns).
- Note
- Returns a dynamically allocated Kernel, which has to be deleted by the caller to avoid memory leaks.
Implements theplu::yat::classifier::Kernel.
An interface for making new classifier objects. This function allows for specification at run-time of which kernel to instatiate (see 'Prototype' in Design Patterns).
- Note
- Returns a dynamically allocated Kernel, which has to be deleted by the caller to avoid memory leaks.
Implements theplu::yat::classifier::Kernel.
double theplu::yat::classifier::Kernel_MEV::operator() |
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const size_t |
row, |
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const size_t |
column |
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virtual |
bool theplu::yat::classifier::Kernel::weighted |
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void |
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const |
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inherited |
- Returns
- true if kernel is calculated using weights
unsigned int* theplu::yat::classifier::Kernel::ref_count_ |
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protectedinherited |
pointer telling how many owners to underlying data (data_). NULL if this is not an owner.
unsigned int* theplu::yat::classifier::Kernel::ref_count_w_ |
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protectedinherited |
pointer telling how many owners to underlying weights (data_w_). NULL if this is not an owner.
The documentation for this class was generated from the following file: