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<html><head><title>dlib C++ Library - spectral_cluster_abstract.h</title></head><body bgcolor='white'><pre> |
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<font color='#009900'>// Copyright (C) 2015 Davis E. King ([email protected]) |
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</font><font color='#009900'>// License: Boost Software License See LICENSE.txt for the full license. |
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</font><font color='#0000FF'>#undef</font> DLIB_SPECTRAL_CLUSTEr_ABSTRACT_H_ |
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<font color='#0000FF'>#ifdef</font> DLIB_SPECTRAL_CLUSTEr_ABSTRACT_H_ |
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<font color='#0000FF'>#include</font> <font color='#5555FF'><</font>vector<font color='#5555FF'>></font> |
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<font color='#0000FF'>namespace</font> dlib |
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<b>{</b> |
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<font color='#0000FF'>template</font> <font color='#5555FF'><</font> |
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<font color='#0000FF'>typename</font> kernel_type, |
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<font color='#0000FF'>typename</font> vector_type |
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<font color='#5555FF'>></font> |
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std::vector<font color='#5555FF'><</font><font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font><font color='#5555FF'>></font> <b><a name='spectral_cluster'></a>spectral_cluster</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> kernel_type<font color='#5555FF'>&</font> k, |
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<font color='#0000FF'>const</font> vector_type<font color='#5555FF'>&</font> samples, |
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<font color='#0000FF'>const</font> <font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> num_clusters |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- samples must be something with an interface compatible with std::vector. |
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- The following expression must evaluate to a double or float: |
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k(samples[i], samples[j]) |
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- num_clusters > 0 |
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ensures |
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- Performs the spectral clustering algorithm described in the paper: |
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On spectral clustering: Analysis and an algorithm by Ng, Jordan, and Weiss. |
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and returns the results. |
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- This function clusters the input data samples into num_clusters clusters and |
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returns a vector that indicates which cluster each sample falls into. In |
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particular, we return an array A such that: |
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- A.size() == samples.size() |
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- A[i] == the cluster assignment of samples[i]. |
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- for all valid i: 0 <= A[i] < num_clusters |
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- The "similarity" of samples[i] with samples[j] is given by |
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k(samples[i],samples[j]). This means that k() should output a number >= 0 |
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and the number should be larger for samples that are more similar. |
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!*/</font> |
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<b>}</b> |
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<font color='#0000FF'>#endif</font> <font color='#009900'>// DLIB_SPECTRAL_CLUSTEr_ABSTRACT_H_ |
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</font> |
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</pre></body></html> |
