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OpenDAS
dlib
Commits
e64b7e74
Commit
e64b7e74
authored
Dec 03, 2011
by
Davis King
Browse files
updated docs
parent
e61caca3
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124 additions
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4 deletions
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-4
docs/docs/ml.xml
docs/docs/ml.xml
+116
-4
docs/docs/term_index.xml
docs/docs/term_index.xml
+8
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docs/docs/ml.xml
View file @
e64b7e74
...
...
@@ -97,14 +97,21 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<sub>
<item>
structural_svm_sequence_labeling_problem
</item>
<item>
structural_svm_object_detection_problem
</item>
<item>
structural_svm_assignment_problem
</item>
</sub>
</item>
<item
nolink=
"true"
>
<name>
Core Tools
</name>
<sub>
<item>
structural_svm_problem
</item>
<item>
structural_object_detection_trainer
</item>
<item>
structural_sequence_labeling_trainer
</item>
<item>
structural_svm_problem_threaded
</item>
<item>
svm_struct_controller_node
</item>
<item>
svm_struct_processing_node
</item>
</sub>
</item>
<item>
structural_object_detection_trainer
</item>
<item>
structural_sequence_labeling_trainer
</item>
<item>
structural_assignment_trainer
</item>
</section>
<section>
<name>
Unsupervised
</name>
...
...
@@ -153,11 +160,13 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
cross_validate_multiclass_trainer
</item>
<item>
cross_validate_regression_trainer
</item>
<item>
cross_validate_sequence_labeler
</item>
<item>
cross_validate_assignment_trainer
</item>
<item>
test_binary_decision_function
</item>
<item>
test_multiclass_decision_function
</item>
<item>
test_regression_function
</item>
<item>
test_object_detection_function
</item>
<item>
test_sequence_labeler
</item>
<item>
test_assignment_function
</item>
</section>
<section>
...
...
@@ -203,6 +212,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
multiclass_linear_decision_function
</item>
<item>
one_vs_all_decision_function
</item>
<item>
sequence_labeler
</item>
<item>
assignment_function
</item>
</section>
<section>
...
...
@@ -220,6 +230,8 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
randomize_samples
</item>
<item>
is_binary_classification_problem
</item>
<item>
is_sequence_labeling_problem
</item>
<item>
is_assignment_problem
</item>
<item>
is_forced_assignment_problem
</item>
<item>
approximate_distance_function
</item>
<item>
is_learning_problem
</item>
<item>
select_all_distinct_labels
</item>
...
...
@@ -1329,6 +1341,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
assignment_function
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/assignment_function_abstract.h
</spec_file>
<description>
This object is a tool for solving the optimal assignment problem given a
user defined method for computing the quality of any particular assignment.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
@@ -1562,6 +1587,32 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
is_assignment_problem
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/svm_abstract.h
</spec_file>
<description>
This function takes a set of training data for an assignment problem
and reports back if it could possibly be a well formed assignment problem.
</description>
</component>
<!-- ************************************************************************* -->
<component>
<name>
is_forced_assignment_problem
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/svm_abstract.h
</spec_file>
<description>
This function takes a set of training data for a forced assignment problem
and reports back if it could possibly be a well formed forced assignment problem.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
@@ -2112,6 +2163,20 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
cross_validate_assignment_trainer
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/cross_validate_assignment_trainer_abstract.h
</spec_file>
<description>
Performs k-fold cross validation on a user supplied assignment trainer object such
as the
<a
href=
"#structural_assignment_trainer"
>
structural_assignment_trainer
</a>
and returns the fraction of assignments predicted correctly.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
@@ -2128,6 +2193,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
test_assignment_function
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/cross_validate_assignment_trainer_abstract.h
</spec_file>
<description>
Tests an
<a
href=
"#assignment_function"
>
assignment_function
</a>
on a set of data
and returns the fraction of assignments predicted correctly.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
@@ -2289,6 +2367,21 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
structural_svm_assignment_problem
</name>
<file>
dlib/svm_threaded.h
</file>
<spec_file
link=
"true"
>
dlib/svm/structural_svm_assignment_problem_abstract.h
</spec_file>
<description>
This object is a tool for learning the weight vector needed to use
an
<a
href=
"#assignment_function"
>
assignment_function
</a>
object.
It learns the parameter vector by
formulating the problem as a
<a
href=
"#structural_svm_problem"
>
structural SVM problem
</a>
.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
@@ -2335,6 +2428,25 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>
structural_assignment_trainer
</name>
<file>
dlib/svm_threaded.h
</file>
<spec_file
link=
"true"
>
dlib/svm/structural_assignment_trainer_abstract.h
</spec_file>
<description>
This object is a tool for learning to solve the assignment problem based
on a set of training data. The training procedure produces an
<a
href=
"#assignment_function"
>
assignment_function
</a>
object
which can be used to predict the assignments of new data.
Note that this is just a convenience wrapper around the
<a
href=
"#structural_svm_assignment_problem"
>
structural_svm_assignment_problem
</a>
to make it look similar to all the other trainers in dlib.
</description>
</component>
<!-- ************************************************************************* -->
<component>
...
...
docs/docs/term_index.xml
View file @
e64b7e74
...
...
@@ -44,6 +44,14 @@
<term
file=
"ml.html"
name=
"structural_svm_sequence_labeling_problem"
/>
<term
file=
"ml.html"
name=
"structural_sequence_labeling_trainer"
/>
<term
file=
"ml.html"
name=
"is_forced_assignment_problem"
/>
<term
file=
"ml.html"
name=
"is_assignment_problem"
/>
<term
file=
"ml.html"
name=
"assignment_function"
/>
<term
file=
"ml.html"
name=
"test_assignment_function"
/>
<term
file=
"ml.html"
name=
"cross_validate_assignment_trainer"
/>
<term
file=
"ml.html"
name=
"structural_svm_assignment_problem"
/>
<term
file=
"ml.html"
name=
"structural_assignment_trainer"
/>
<term
file=
"dlib/optimization/optimization_solve_qp2_using_smo_abstract.h.html"
name=
"invalid_nu_error"
/>
<term
file=
"dlib/optimization/optimization_solve_qp2_using_smo_abstract.h.html"
name=
"maximum_nu"
/>
...
...
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