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Commit 47cfecb5 authored by Davis King's avatar Davis King
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Updated docs 

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docs/docs/ml.xml
View file @ 47cfecb5
......@@ -82,6 +82,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>rbf_network_trainer</item>
<item>rank_features</item>
<item>svm_pegasos</item>
<item>one_vs_one_trainer</item>
</section>
<section>
......@@ -119,6 +120,7 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>distance_function</item>
<item>probabilistic_decision_function</item>
<item>normalized_function</item>
<item>one_vs_one_decision_function</item>
</section>
<section>
......@@ -128,6 +130,15 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
<item>sparse_to_dense</item>
</section>
<section>
<name>Validation</name>
<item>cross_validate_trainer</item>
<item>cross_validate_trainer_threaded</item>
<item>cross_validate_multiclass_trainer</item>
<item>test_binary_decision_function</item>
<item>test_multiclass_decision_function</item>
</section>
<section>
<name>Miscellaneous</name>
<item>simplify_linear_decision_function</item>
......@@ -140,9 +151,7 @@ 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_learning_problem</item>
<item>test_binary_decision_function</item>
<item>cross_validate_trainer</item>
<item>cross_validate_trainer_threaded</item>
<item>select_all_distinct_labels</item>
<item>pick_initial_centers</item>
<item>find_gamma_with_big_centroid_gap</item>
<item>compute_mean_squared_distance</item>
......@@ -1121,6 +1130,38 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>one_vs_one_decision_function</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/one_vs_one_decision_function_abstract.h</spec_file>
<description>
This object represents a multiclass classifier built out
of a set of binary classifiers. Each binary classifier
is used to vote for the correct multiclass label using a
one vs. one strategy. Therefore, if you have N classes then
there will be N*(N-1)/2 binary classifiers inside this object.
</description>
</component>
<!-- ************************************************************************* -->
<component>
<name>one_vs_one_trainer</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/one_vs_one_trainer_abstract.h</spec_file>
<description>
This object is a tool for turning a bunch of binary classifiers
into a multiclass classifier. It does this by training the binary
classifiers in a one vs. one fashion. That is, if you have N possible
classes then it trains N*(N-1)/2 binary classifiers which are then used
to vote on the identity of a test sample.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -1298,6 +1339,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>select_all_distinct_labels</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/multiclass_tools_abstract.h</spec_file>
<description>
This is a function which determines all distinct values present in a
std::vector and returns the result.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -1681,6 +1735,19 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>test_multiclass_decision_function</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/cross_validate_multiclass_trainer_abstract.h</spec_file>
<description>
Tests a multiclass decision function (e.g. <a href="#one_vs_one_decision_function">one_vs_one_decision_function</a>)
and returns a confusion matrix describing the results.
</description>
</component>
<!-- ************************************************************************* -->
......@@ -1715,6 +1782,20 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
</component>
<!-- ************************************************************************* -->
<component>
<name>cross_validate_multiclass_trainer</name>
<file>dlib/svm.h</file>
<spec_file link="true">dlib/svm/cross_validate_multiclass_trainer_abstract.h</spec_file>
<description>
Performs k-fold cross validation on a user supplied multiclass classification trainer object such
as the <a href="#one_vs_one_trainer">one_vs_one_trainer</a>. The result is described by a
confusion matrix.
</description>
</component>
<!-- ************************************************************************* -->
</components>
......
docs/docs/term_index.xml
View file @ 47cfecb5
......@@ -126,6 +126,12 @@
<term file="algorithms.html" name="random_subset_selector"/>
<term file="algorithms.html" name="randomly_subsample"/>
<term file="ml.html" name="select_all_distinct_labels"/>
<term file="dlib/svm/multiclass_tools_abstract.h.html#find_missing_pairs" name="find_missing_pairs"/>
<term file="ml.html" name="one_vs_one_trainer"/>
<term file="ml.html" name="one_vs_one_decision_function"/>
<term file="dlib/svm/pegasos_abstract.h.html" name="replicate_settings"/>
<term file="ml.html" name="mlp"/>
<term file="ml.html" name="load_libsvm_formatted_data"/>
......@@ -182,7 +188,9 @@
<term file="ml.html" name="train_probabilistic_decision_function"/>
<term file="ml.html" name="cross_validate_trainer"/>
<term file="ml.html" name="cross_validate_trainer_threaded"/>
<term file="ml.html" name="cross_validate_multiclass_trainer"/>
<term file="ml.html" name="test_binary_decision_function"/>
<term file="ml.html" name="test_multiclass_decision_function"/>
<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#krr_trainer" name="kernel ridge regression"/>
......
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