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Made the spec more clear. 

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extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403343
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Davis King 2010-01-01 20:39:11 +00:00
parent 1408d57181
commit d3ecb34d99
1 changed files with 7 additions and 8 deletions
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15
dlib/svm/empirical_kernel_map_abstract.h
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@ -173,10 +173,10 @@ namespace dlib
- takes the given sample and projects it into the kernel feature space
of out_vector_size() dimensions defined by this kernel map and
returns the resulting vector.
- in more precise terms, this function returns a vector V such that:
- V.size() == out_vector_size()
- in more precise terms, this function returns a vector such that:
- The returned vector will contain out_vector_size() elements.
- for any sample_type object S, the following equality is approximately true:
- get_kernel()(sample,S) == dot(V, project(S)).
- get_kernel()(sample,S) == dot(project(sample), project(S)).
- The approximation error in the above equality will be zero (within rounding error)
if both sample_type objects involved are within the span of the set of basis
samples given to the load() function. If they are not then there will be some
@ -226,11 +226,10 @@ namespace dlib
(i.e. the returned distance function computes distances, in kernel feature space,
between vect and any argument you give it. )
- The approximation error in the above equality will be zero (within rounding error)
if both sample_type objects involved are within the span of the set of basis
samples given to the load() function. If they are not then there will be some
approximation error. Note that all the basis samples are always within their
own span. So the equality is always exact for the samples given to the load()
function.
if S is within the span of the set of basis samples given to the load() function.
If it is not then there will be some approximation error. Note that all the basis
samples are always within their own span. So the equality is always exact for the
samples given to the load() function.
- DF.kernel_function == get_kernel()
- DF.b == dot(vect,vect)
- DF.basis_vectors == these will be the basis samples given to the previous call to load(). Note