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Added the distance_function object
--HG-- extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402387
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Davis King
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@ -231,6 +231,144 @@ namespace dlib
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}
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}
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// ----------------------------------------------------------------------------------------
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template <
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typename K
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>
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struct distance_function
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{
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typedef typename K::scalar_type scalar_type;
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typedef typename K::sample_type sample_type;
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typedef typename K::mem_manager_type mem_manager_type;
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typedef matrix<scalar_type,0,1,mem_manager_type> scalar_vector_type;
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typedef matrix<sample_type,0,1,mem_manager_type> sample_vector_type;
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const scalar_vector_type alpha;
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const scalar_type b;
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const K kernel_function;
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const sample_vector_type support_vectors;
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distance_function (
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) : b(0), kernel_function(K()) {}
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distance_function (
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const distance_function& d
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) :
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alpha(d.alpha),
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b(d.b),
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kernel_function(d.kernel_function),
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support_vectors(d.support_vectors)
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{}
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distance_function (
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const scalar_vector_type& alpha_,
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const scalar_type& b_,
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const K& kernel_function_,
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const sample_vector_type& support_vectors_
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) :
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alpha(alpha_),
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b(b_),
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kernel_function(kernel_function_),
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support_vectors(support_vectors_)
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{}
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distance_function& operator= (
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const distance_function& d
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)
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{
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if (this != &d)
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{
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const_cast<scalar_vector_type&>(alpha) = d.alpha;
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const_cast<scalar_type&>(b) = d.b;
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const_cast<K&>(kernel_function) = d.kernel_function;
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const_cast<sample_vector_type&>(support_vectors) = d.support_vectors;
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}
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return *this;
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}
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scalar_type operator() (
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const sample_type& x
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) const
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{
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scalar_type temp = 0;
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for (long i = 0; i < alpha.nr(); ++i)
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temp += alpha(i) * kernel_function(x,support_vectors(i));
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temp = b + kernel_function(x,x) - 2*temp;
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if (temp > 0)
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return std::sqrt(temp);
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else
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return 0;
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}
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scalar_type operator() (
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const distance_function& x
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) const
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{
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scalar_type temp = 0;
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for (long i = 0; i < alpha.nr(); ++i)
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for (long j = 0; j < x.alpha.nr(); ++j)
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temp += alpha(i)*x.alpha(j) * kernel_function(support_vectors(i), x.support_vectors(j));
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temp = b + x.b - 2*temp;
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if (temp > 0)
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return std::sqrt(temp);
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else
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return 0;
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}
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};
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template <
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typename K
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>
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void serialize (
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const distance_function<K>& item,
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std::ostream& out
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)
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{
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try
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{
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serialize(item.alpha, out);
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serialize(item.b, out);
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serialize(item.kernel_function, out);
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serialize(item.support_vectors, out);
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}
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catch (serialization_error e)
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{
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throw serialization_error(e.info + "\n while serializing object of type distance_function");
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}
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}
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template <
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typename K
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>
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void deserialize (
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distance_function<K>& item,
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std::istream& in
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)
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{
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typedef typename K::scalar_type scalar_type;
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typedef typename K::sample_type sample_type;
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typedef typename K::mem_manager_type mem_manager_type;
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typedef matrix<scalar_type,0,1,mem_manager_type> scalar_vector_type;
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typedef matrix<sample_type,0,1,mem_manager_type> sample_vector_type;
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try
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{
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deserialize(const_cast<scalar_vector_type&>(item.alpha), in);
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deserialize(const_cast<scalar_type&>(item.b), in);
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deserialize(const_cast<K&>(item.kernel_function), in);
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deserialize(const_cast<sample_vector_type&>(item.support_vectors), in);
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}
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catch (serialization_error e)
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{
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throw serialization_error(e.info + "\n while deserializing object of type distance_function");
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}
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}
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// ----------------------------------------------------------------------------------------
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}
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@ -93,7 +93,7 @@ namespace dlib
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for (long i = 0; i < alpha.nr(); ++i)
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temp += alpha(i) * kernel_function(x,support_vectors(i));
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returns temp - b;
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return temp - b;
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}
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};
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@ -225,6 +225,141 @@ namespace dlib
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// ----------------------------------------------------------------------------------------
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template <
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typename K
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>
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struct distance_function
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{
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/*!
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REQUIREMENTS ON K
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K must be a kernel function object type as defined at the
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top of dlib/svm/kernel_abstract.h
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WHAT THIS OBJECT REPRESENTS
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This object represents a point in kernel induced feature space.
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You may use this object to find the distance from the point it
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represents to points in input space.
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!*/
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typedef typename K::scalar_type scalar_type;
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typedef typename K::sample_type sample_type;
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typedef typename K::mem_manager_type mem_manager_type;
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typedef matrix<scalar_type,0,1,mem_manager_type> scalar_vector_type;
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typedef matrix<sample_type,0,1,mem_manager_type> sample_vector_type;
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const scalar_vector_type alpha;
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const scalar_type b;
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const K kernel_function;
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const sample_vector_type support_vectors;
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distance_function (
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);
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/*!
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ensures
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- #b == 0
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- #alpha.nr() == 0
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- #support_vectors.nr() == 0
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!*/
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distance_function (
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const distance_function& f
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);
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/*!
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ensures
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- #*this is a copy of f
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!*/
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distance_function (
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const scalar_vector_type& alpha_,
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const scalar_type& b_,
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const K& kernel_function_,
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const sample_vector_type& support_vectors_
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) : alpha(alpha_), b(b_), kernel_function(kernel_function_), support_vectors(support_vectors_) {}
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/*!
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ensures
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- populates the decision function with the given support vectors, weights(i.e. alphas),
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b term, and kernel function.
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!*/
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distance_function& operator= (
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const distance_function& d
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);
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/*!
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ensures
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- #*this is identical to d
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- returns *this
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!*/
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scalar_type operator() (
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const sample_type& x
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) const
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/*!
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ensures
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- Let O(x) represent the point x projected into kernel induced feature space.
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- let c == sum alpha(i)*O(support_vectors(i)) == the point in kernel space that
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this object represents.
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- Then this object returns the distance between the points O(x) and c in kernel
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space.
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!*/
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{
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scalar_type temp = 0;
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for (long i = 0; i < alpha.nr(); ++i)
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temp += alpha(i) * kernel_function(x,support_vectors(i));
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temp = b + kernel_function(x,x) - 2*temp;
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if (temp > 0)
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return std::sqrt(temp);
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else
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return 0;
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}
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scalar_type operator() (
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const distance_function& x
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) const
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/*!
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ensures
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- returns the distance between the point in kernel space represented by *this and x.
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!*/
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{
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scalar_type temp = 0;
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for (long i = 0; i < alpha.nr(); ++i)
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for (long j = 0; j < x.alpha.nr(); ++j)
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temp += alpha(i)*x.alpha(j) * kernel_function(support_vectors(i), x.support_vectors(j));
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temp = b + x.b - 2*temp;
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if (temp > 0)
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return std::sqrt(temp);
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else
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return 0;
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}
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};
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template <
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typename K
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>
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void serialize (
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const distance_function<K>& item,
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std::ostream& out
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);
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/*!
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provides serialization support for distance_function
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!*/
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template <
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typename K
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>
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void deserialize (
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distance_function<K>& item,
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std::istream& in
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);
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/*!
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provides serialization support for distance_function
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!*/
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// ----------------------------------------------------------------------------------------
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}
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#endif // DLIB_SVm_FUNCTION_ABSTRACT_
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@ -215,6 +215,16 @@ namespace dlib
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item.bias_is_stale = true;
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}
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distance_function<kernel_type> get_distance_function (
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) const
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{
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refresh_bias();
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return distance_function<kernel_type>(vector_to_matrix(alpha),
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bias,
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kernel,
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vector_to_matrix(dictionary));
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}
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private:
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void refresh_bias (
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@ -193,6 +193,16 @@ namespace dlib
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- returns the number of "support vectors" in the dictionary.
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!*/
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distance_function<kernel_type> get_distance_function (
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) const;
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/*!
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ensures
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- returns a distance function F that represents the point learned
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by this object so far. I.e. it is the case that:
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- for all x: F(x) == (*this)(x)
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!*/
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};
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// ----------------------------------------------------------------------------------------
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