EPS@ISEP | The European Project Semester (EPS) at ISEP


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example [2015/06/23 19:02] – [Refnotes Plugin Usage Examples] epsatisepexample [2019/04/07 13:32] (current) – [MathJax Plugin Usage Example] team2
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 ==== Refnotes Plugin Usage Examples ==== ==== Refnotes Plugin Usage Examples ====
  
-This is a reference to a book [(Mulder2013428)] [(bandyopadhyay2013unsupervised)], a Web resource [(android41)] and to an article [(llorente2009virtual)]. This is a test  [(cloudexpo2008)], [(Commission2015)].+This is a reference to a book [(Mulder2013428)] [(bandyopadhyay2013unsupervised)], a Web resource [(android41)] and to an article [(llorente2009virtual)]. This is a test  [(cloudexpo2008)], [(Commission2015)] and [(ref2me)].
  
 Please use superscript and subscript annotations to write powers and indexes, //e.g.//, m<sup>2</sup> and CO<sub>2</sub>. Please use superscript and subscript annotations to write powers and indexes, //e.g.//, m<sup>2</sup> and CO<sub>2</sub>.
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 Equation \ref{eq:cosinesimilarity} represents the cosine similarity between two vectors of features. This similarity measurement takes values in the range of $[0,1]$ [(bandyopadhyay2013unsupervised)]. Equation \ref{eq:cosinesimilarity} represents the cosine similarity between two vectors of features. This similarity measurement takes values in the range of $[0,1]$ [(bandyopadhyay2013unsupervised)].
 +This is an in line expression $a+b=c$.
  
 <WRAP centeralign> <WRAP centeralign>
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      \label{eq:cosinesimilarity}      \label{eq:cosinesimilarity}
 \end{equation} \end{equation}
-</WRAP>+</WRAP>\frac
  
 As [(bandyopadhyay2013unsupervised)] states, the most popular similarity metrics are the distance and the cosine similarity. The distance-based metrics include the Euclidean distance, the Hamming distance or the Chebyshev distance, among others. As [(bandyopadhyay2013unsupervised)] states, the most popular similarity metrics are the distance and the cosine similarity. The distance-based metrics include the Euclidean distance, the Hamming distance or the Chebyshev distance, among others.
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