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updated docs

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docs/docs/ml.xml
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......@@ -116,6 +116,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</item>
<item>structural_object_detection_trainer</item>
<item>structural_sequence_labeling_trainer</item>
<item>structural_sequence_segmentation_trainer</item>
<item>structural_assignment_trainer</item>
<item>structural_graph_labeling_trainer</item>
<item>svm_rank_trainer</item>
......@@ -161,6 +162,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>cross_validate_multiclass_trainer</item>
<item>cross_validate_regression_trainer</item>
<item>cross_validate_sequence_labeler</item>
<item>cross_validate_sequence_segmenter</item>
<item>cross_validate_assignment_trainer</item>
<item>cross_validate_graph_labeling_trainer</item>
<item>cross_validate_ranking_trainer</item>
......@@ -169,6 +171,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>test_regression_function</item>
<item>test_object_detection_function</item>
<item>test_sequence_labeler</item>
<item>test_sequence_segmenter</item>
<item>test_assignment_function</item>
<item>test_graph_labeling_function</item>
<item>test_ranking_function</item>
......@@ -218,6 +221,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>multiclass_linear_decision_function</item>
<item>one_vs_all_decision_function</item>
<item>sequence_labeler</item>
<item>sequence_segmenter</item>
<item>assignment_function</item>
<item>graph_labeler</item>
</section>
......@@ -239,6 +243,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<item>randomize_samples</item>
<item>is_binary_classification_problem</item>
<item>is_sequence_labeling_problem</item>
<item>is_sequence_segmentation_problem</item>
<item>is_graph_labeling_problem</item>
<item>is_assignment_problem</item>
<item>is_forced_assignment_problem</item>
......@@ -1447,6 +1452,29 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>sequence_segmenter</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/sequence_segmenter_abstract.h</spec_file>
<description>
This object is a tool for segmenting a sequence of objects into a set of
non-overlapping chunks. An example sequence segmentation task is to take
English sentences and identify all the named entities. In this example,
you would be using a sequence_segmenter to find all the chunks of
contiguous words which refer to proper names.
<p>
The sequence_segmenter is implemented using the BIO (Begin, Inside,
Outside) sequence tagging model. Moreover, the sequence tagging is done
internally using a <a href="#sequence_labeler">sequence_labeler</a> object
and therefore sequence_segmenter objects are examples of chain structured
conditional random field style sequence taggers.
</p>
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -1728,6 +1756,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>is_sequence_segmentation_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 segmentation problem
and reports back if it could possibly be a well formed sequence segmentation problem.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -2357,6 +2398,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>cross_validate_sequence_segmenter</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/cross_validate_sequence_segmenter_abstract.h</spec_file>
<description>
Performs k-fold cross validation on a user supplied sequence segmentation trainer object such
as the <a href="#structural_sequence_segmentation_trainer">structural_sequence_segmentation_trainer</a>
and returns the resulting precision, recall, and F1-score.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -2425,6 +2479,18 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>test_sequence_segmenter</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/cross_validate_sequence_segmenter_abstract.h</spec_file>
<description>
Tests a <a href="#sequence_segmenter">sequence_segmenter</a> on a set of data
and returns the resulting precision, recall, and F1-score.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -2730,6 +2796,24 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
</component>
<!-- ************************************************************************* -->
<component>
<name>structural_sequence_segmentation_trainer</name>
<file>dlib/svm_threaded.h</file>
<spec_file link="true">dlib/svm/structural_sequence_segmentation_trainer_abstract.h</spec_file>
<description>
This object is a tool for learning to do sequence segmentation based on a
set of training data. The training procedure produces a <a href="#sequence_segmenter">sequence_segmenter</a>
object which can be used to identify the sub-segments of new data sequences.
<p>
This object internally uses the <a href="#structural_sequence_labeling_trainer">structural_sequence_labeling_trainer</a>
to solve the learning problem.
</p>
</description>
</component>
<!-- ************************************************************************* -->
<component>
......
docs/docs/term_index.xml
View file @ 1b093f7a
......@@ -60,6 +60,10 @@
<term file="ml.html" name="structural_svm_sequence_labeling_problem" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="structural_sequence_labeling_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="sequence_segmenter" include="dlib/svm.h"/>
<term file="dlib/svm/sequence_segmenter_abstract.h.html" name="total_feature_vector_size" include="dlib/svm.h"/>
<term file="ml.html" name="structural_sequence_segmentation_trainer" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="is_forced_assignment_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_assignment_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_graph_labeling_problem" include="dlib/svm_threaded.h"/>
......@@ -298,6 +302,7 @@
<term file="ml.html" name="simplify_linear_decision_function" include="dlib/svm.h"/>
<term file="ml.html" name="is_binary_classification_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_sequence_labeling_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_sequence_segmentation_problem" include="dlib/svm.h"/>
<term file="ml.html" name="is_learning_problem" include="dlib/svm.h"/>
<term file="ml.html" name="svm_nu_trainer" include="dlib/svm.h"/>
<term file="ml.html" name="svm_c_trainer" include="dlib/svm.h"/>
......@@ -329,6 +334,7 @@
<term file="ml.html" name="cross_validate_trainer" include="dlib/svm.h"/>
<term file="ml.html" name="cross_validate_object_detection_trainer" include="dlib/svm.h"/>
<term file="ml.html" name="cross_validate_sequence_labeler" include="dlib/svm.h"/>
<term file="ml.html" name="cross_validate_sequence_segmenter" include="dlib/svm.h"/>
<term file="ml.html" name="cross_validate_trainer_threaded" include="dlib/svm_threaded.h"/>
<term file="ml.html" name="cross_validate_multiclass_trainer" include="dlib/svm.h"/>
<term file="dlib/svm/cross_validate_multiclass_trainer_abstract.h.html" name="cross_validation_error" include="dlib/svm.h"/>
......@@ -338,6 +344,7 @@
<term file="ml.html" name="test_multiclass_decision_function" include="dlib/svm.h"/>
<term file="ml.html" name="test_regression_function" include="dlib/svm.h"/>
<term file="ml.html" name="test_sequence_labeler" include="dlib/svm.h"/>
<term file="ml.html" name="test_sequence_segmenter" include="dlib/svm.h"/>
<term link="ml.html#svm_nu_trainer" name="support vector machine" include="dlib/svm.h"/>
<term link="ml.html#rvm_trainer" name="relevance vector machine" include="dlib/svm.h"/>
<term link="ml.html#krr_trainer" name="kernel ridge regression" include="dlib/svm.h"/>
......
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