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@ -9,25 +9,9 @@
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<body>
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<br/><br/>
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<a href="ml_guide.svg"><img src="ml_guide.svg" width="100%"/></a>
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<p>
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This page documents all the machine learning algorithms present in
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the library. In particular, there are algorithms for performing
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classification, regression, clustering, sequence labeling, assignment learning,
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rank learning, graph segmentation, object detection, anomaly detection,
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and feature ranking, as well as algorithms for doing more
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specialized computations.
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</p>
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<p>
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A good tutorial and introduction to the general concepts used by most of the
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objects in this part of the library can be found in the <a href="svm_ex.cpp.html">svm example</a> program.
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After reading this example another good one to consult would be the <a href="model_selection_ex.cpp.html">model selection</a>
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example program. Finally, if you came here looking for a binary classification or regression tool then I would
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try the <a href="#krr_trainer">krr_trainer</a> first as it is generally the easiest method to use.
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</p>
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<p>
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The major design goal of this portion of the library is to provide a highly modular and
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A major design goal of this portion of the library is to provide a highly modular and
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simple architecture for dealing with kernel algorithms. Towards this end, dlib takes a generic
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programming approach using C++ templates. In particular, each algorithm is parameterized
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to allow a user to supply either one of the predefined dlib kernels (e.g. <a
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@ -41,7 +25,6 @@
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</p>
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<br/>
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<h3>Paper Describing dlib Machine Learning</h3>
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<pre>
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Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09a.pdf">Dlib-ml: A Machine Learning Toolkit</a>.
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@ -470,6 +453,11 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
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regression algorithm. You give it samples (x,y) and it learns the function
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f(x) == y. For a detailed description of the algorithm read the above paper.
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</p>
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<p>
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Note that if you want to use the linear kernel then you would
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be better off using the <a href="#rls">rls</a> object as it
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is optimized for this case.
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</p>
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</description>
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<examples>
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@ -554,6 +542,10 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
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<description>
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This is an implementation of a kernelized k-means clustering algorithm.
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It performs k-means clustering by using the <a href="#kcentroid">kcentroid</a> object.
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<p>
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If you want to use the linear kernel (i.e. do a normal k-means clustering) then you
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should use the <a href="#find_clusters_using_kmeans">find_clusters_using_kmeans</a> routine.
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</p>
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</description>
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<examples>
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Davis King
11 years ago
