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OpenDAS
dlib
Commits
bf27b070
Commit
bf27b070
authored
Oct 30, 2011
by
Davis King
Browse files
updated docs
parent
4fd423a5
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docs/docs/index.xml
docs/docs/index.xml
+1
-0
docs/docs/ml.xml
docs/docs/ml.xml
+100
-1
docs/docs/term_index.xml
docs/docs/term_index.xml
+6
-0
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docs/docs/index.xml
View file @
bf27b070
...
@@ -141,6 +141,7 @@
...
@@ -141,6 +141,7 @@
<li>
A kernelized
<a
href=
"ml.html#kkmeans"
>
k-means
</a>
clustering algorithm
</li>
<li>
A kernelized
<a
href=
"ml.html#kkmeans"
>
k-means
</a>
clustering algorithm
</li>
<li><a
href=
"ml.html#rbf_network_trainer"
>
Radial Basis Function Networks
</a></li>
<li><a
href=
"ml.html#rbf_network_trainer"
>
Radial Basis Function Networks
</a></li>
<li><a
href=
"ml.html#mlp"
>
Multi layer perceptrons
</a>
</li>
<li><a
href=
"ml.html#mlp"
>
Multi layer perceptrons
</a>
</li>
<li><a
href=
"ml.html#structural_sequence_labeling_trainer"
>
Sequence labeling
</a>
</li>
</ul>
</ul>
</li>
</li>
...
...
docs/docs/ml.xml
View file @
bf27b070
...
@@ -92,9 +92,16 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -92,9 +92,16 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</section>
</section>
<section>
<section>
<name>
Structured Prediction
</name>
<name>
Structured Prediction
</name>
<item
nolink=
"true"
>
<name>
Problem Instances
</name>
<sub>
<item>
structural_svm_sequence_labeling_problem
</item>
<item>
structural_svm_object_detection_problem
</item>
</sub>
</item>
<item>
structural_svm_problem
</item>
<item>
structural_svm_problem
</item>
<item>
structural_svm_object_detection_problem
</item>
<item>
structural_object_detection_trainer
</item>
<item>
structural_object_detection_trainer
</item>
<item>
structural_sequence_labeling_trainer
</item>
<item>
structural_svm_problem_threaded
</item>
<item>
structural_svm_problem_threaded
</item>
<item>
svm_struct_controller_node
</item>
<item>
svm_struct_controller_node
</item>
<item>
svm_struct_processing_node
</item>
<item>
svm_struct_processing_node
</item>
...
@@ -145,10 +152,12 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -145,10 +152,12 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
cross_validate_trainer_threaded
</item>
<item>
cross_validate_trainer_threaded
</item>
<item>
cross_validate_multiclass_trainer
</item>
<item>
cross_validate_multiclass_trainer
</item>
<item>
cross_validate_regression_trainer
</item>
<item>
cross_validate_regression_trainer
</item>
<item>
cross_validate_sequence_labeler
</item>
<item>
test_binary_decision_function
</item>
<item>
test_binary_decision_function
</item>
<item>
test_multiclass_decision_function
</item>
<item>
test_multiclass_decision_function
</item>
<item>
test_regression_function
</item>
<item>
test_regression_function
</item>
<item>
test_object_detection_function
</item>
<item>
test_object_detection_function
</item>
<item>
test_sequence_labeler
</item>
</section>
</section>
<section>
<section>
...
@@ -191,6 +200,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -191,6 +200,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
one_vs_one_decision_function
</item>
<item>
one_vs_one_decision_function
</item>
<item>
multiclass_linear_decision_function
</item>
<item>
multiclass_linear_decision_function
</item>
<item>
one_vs_all_decision_function
</item>
<item>
one_vs_all_decision_function
</item>
<item>
sequence_labeler
</item>
</section>
</section>
<section>
<section>
...
@@ -207,6 +217,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -207,6 +217,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>
fill_lisf
</item>
<item>
fill_lisf
</item>
<item>
randomize_samples
</item>
<item>
randomize_samples
</item>
<item>
is_binary_classification_problem
</item>
<item>
is_binary_classification_problem
</item>
<item>
is_sequence_labeling_problem
</item>
<item>
approximate_distance_function
</item>
<item>
approximate_distance_function
</item>
<item>
is_learning_problem
</item>
<item>
is_learning_problem
</item>
<item>
select_all_distinct_labels
</item>
<item>
select_all_distinct_labels
</item>
...
@@ -1291,6 +1302,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -1291,6 +1302,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
</component>
<!-- ************************************************************************* -->
<component>
<name>
sequence_labeler
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/sequence_labeler_abstract.h
</spec_file>
<description>
This object is a tool for labeling each element of a sequence with
a discrete label.
</description>
</component>
<!-- ************************************************************************* -->
<!-- ************************************************************************* -->
<component>
<component>
...
@@ -1501,6 +1525,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -1501,6 +1525,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
</component>
<!-- ************************************************************************* -->
<component>
<name>
is_sequence_labeling_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 sequence labeling problem
and reports back if it could possibly be a well formed sequence labeling problem.
</description>
</component>
<!-- ************************************************************************* -->
<!-- ************************************************************************* -->
<component>
<component>
...
@@ -2034,6 +2071,33 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -2034,6 +2071,33 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
</component>
<!-- ************************************************************************* -->
<component>
<name>
cross_validate_sequence_labeler
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/cross_validate_sequence_labeler_abstract.h
</spec_file>
<description>
Performs k-fold cross validation on a user supplied sequence labeling trainer object such
as the
<a
href=
"#structural_sequence_labeling_trainer"
>
structural_sequence_labeling_trainer
</a>
and returns a confusion matrix describing the results.
</description>
</component>
<!-- ************************************************************************* -->
<component>
<name>
test_sequence_labeler
</name>
<file>
dlib/svm.h
</file>
<spec_file
link=
"true"
>
dlib/svm/cross_validate_sequence_labeler_abstract.h
</spec_file>
<description>
Tests a
<a
href=
"#sequence_labeler"
>
sequence_labeler
</a>
on a set of data
and returns a confusion matrix describing the results.
</description>
</component>
<!-- ************************************************************************* -->
<!-- ************************************************************************* -->
<component>
<component>
...
@@ -2169,6 +2233,24 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -2169,6 +2233,24 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
</component>
<!-- ************************************************************************* -->
<component>
<name>
structural_svm_sequence_labeling_problem
</name>
<file>
dlib/svm_threaded.h
</file>
<spec_file
link=
"true"
>
dlib/svm/structural_svm_sequence_labeling_problem_abstract.h
</spec_file>
<description>
This object is a tool for learning the parameter vector needed to use
a
<a
href=
"#sequence_labeler"
>
sequence_labeler
</a>
object.
<p>
It learns the parameter vector by formulating the problem as a
<a
href=
"#structural_svm_problem"
>
structural
SVM problem
</a>
.
</p>
</description>
</component>
<!-- ************************************************************************* -->
<!-- ************************************************************************* -->
<component>
<component>
...
@@ -2192,6 +2274,23 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
...
@@ -2192,6 +2274,23 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
</component>
<!-- ************************************************************************* -->
<component>
<name>
structural_sequence_labeling_trainer
</name>
<file>
dlib/svm_threaded.h
</file>
<spec_file
link=
"true"
>
dlib/svm/structural_sequence_labeling_trainer_abstract.h
</spec_file>
<description>
This object is a tool for learning to do sequence labeling.
<p>
Note that this is just a convenience wrapper around the
<a
href=
"#structural_svm_sequence_labeling_problem"
>
structural_svm_sequence_labeling_problem
</a>
to make it look similar to all the other trainers in dlib.
</p>
</description>
</component>
<!-- ************************************************************************* -->
<!-- ************************************************************************* -->
<component>
<component>
...
...
docs/docs/term_index.xml
View file @
bf27b070
...
@@ -40,6 +40,9 @@
...
@@ -40,6 +40,9 @@
<term
file=
"ml.html"
name=
"structural_object_detection_trainer"
/>
<term
file=
"ml.html"
name=
"structural_object_detection_trainer"
/>
<term
file=
"ml.html"
name=
"svm_struct_controller_node"
/>
<term
file=
"ml.html"
name=
"svm_struct_controller_node"
/>
<term
file=
"ml.html"
name=
"svm_struct_processing_node"
/>
<term
file=
"ml.html"
name=
"svm_struct_processing_node"
/>
<term
file=
"ml.html"
name=
"sequence_labeler"
/>
<term
file=
"ml.html"
name=
"structural_svm_sequence_labeling_problem"
/>
<term
file=
"ml.html"
name=
"structural_sequence_labeling_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=
"invalid_nu_error"
/>
<term
file=
"dlib/optimization/optimization_solve_qp2_using_smo_abstract.h.html"
name=
"maximum_nu"
/>
<term
file=
"dlib/optimization/optimization_solve_qp2_using_smo_abstract.h.html"
name=
"maximum_nu"
/>
...
@@ -204,6 +207,7 @@
...
@@ -204,6 +207,7 @@
<term
file=
"ml.html"
name=
"randomize_samples"
/>
<term
file=
"ml.html"
name=
"randomize_samples"
/>
<term
file=
"ml.html"
name=
"simplify_linear_decision_function"
/>
<term
file=
"ml.html"
name=
"simplify_linear_decision_function"
/>
<term
file=
"ml.html"
name=
"is_binary_classification_problem"
/>
<term
file=
"ml.html"
name=
"is_binary_classification_problem"
/>
<term
file=
"ml.html"
name=
"is_sequence_labeling_problem"
/>
<term
file=
"ml.html"
name=
"is_learning_problem"
/>
<term
file=
"ml.html"
name=
"is_learning_problem"
/>
<term
file=
"ml.html"
name=
"svm_nu_trainer"
/>
<term
file=
"ml.html"
name=
"svm_nu_trainer"
/>
<term
file=
"ml.html"
name=
"svm_c_trainer"
/>
<term
file=
"ml.html"
name=
"svm_c_trainer"
/>
...
@@ -225,6 +229,7 @@
...
@@ -225,6 +229,7 @@
<term
file=
"ml.html"
name=
"probabilistic"
/>
<term
file=
"ml.html"
name=
"probabilistic"
/>
<term
file=
"ml.html"
name=
"cross_validate_trainer"
/>
<term
file=
"ml.html"
name=
"cross_validate_trainer"
/>
<term
file=
"ml.html"
name=
"cross_validate_object_detection_trainer"
/>
<term
file=
"ml.html"
name=
"cross_validate_object_detection_trainer"
/>
<term
file=
"ml.html"
name=
"cross_validate_sequence_labeler"
/>
<term
file=
"ml.html"
name=
"cross_validate_trainer_threaded"
/>
<term
file=
"ml.html"
name=
"cross_validate_trainer_threaded"
/>
<term
file=
"ml.html"
name=
"cross_validate_multiclass_trainer"
/>
<term
file=
"ml.html"
name=
"cross_validate_multiclass_trainer"
/>
<term
file=
"dlib/svm/cross_validate_multiclass_trainer_abstract.h.html"
name=
"cross_validation_error"
/>
<term
file=
"dlib/svm/cross_validate_multiclass_trainer_abstract.h.html"
name=
"cross_validation_error"
/>
...
@@ -233,6 +238,7 @@
...
@@ -233,6 +238,7 @@
<term
file=
"ml.html"
name=
"test_object_detection_function"
/>
<term
file=
"ml.html"
name=
"test_object_detection_function"
/>
<term
file=
"ml.html"
name=
"test_multiclass_decision_function"
/>
<term
file=
"ml.html"
name=
"test_multiclass_decision_function"
/>
<term
file=
"ml.html"
name=
"test_regression_function"
/>
<term
file=
"ml.html"
name=
"test_regression_function"
/>
<term
file=
"ml.html"
name=
"test_sequence_labeler"
/>
<term
link=
"ml.html#svm_nu_trainer"
name=
"support vector machine"
/>
<term
link=
"ml.html#svm_nu_trainer"
name=
"support vector machine"
/>
<term
link=
"ml.html#rvm_trainer"
name=
"relevance vector machine"
/>
<term
link=
"ml.html#rvm_trainer"
name=
"relevance vector machine"
/>
<term
link=
"ml.html#krr_trainer"
name=
"kernel ridge regression"
/>
<term
link=
"ml.html#krr_trainer"
name=
"kernel ridge regression"
/>
...
...
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