What is this data structure/concept where a plot of points defines a partition to a space












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I encountered an algorithm to solve a real world problem, and I remember a class I took where I made something very similar for some for a homework problem. it looks like this



Basically it's a plot of points, and the lines are drawn to be equidistant between two points. It forms a perfect partition where the lines around the point form the shape of area that is closest to that point. Does this ring a bell to anyone? I've had a tough time googling descriptions and getting results. And I don't know how else to describe it. Hopefully the picture helps.










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    $begingroup$


    I encountered an algorithm to solve a real world problem, and I remember a class I took where I made something very similar for some for a homework problem. it looks like this



    Basically it's a plot of points, and the lines are drawn to be equidistant between two points. It forms a perfect partition where the lines around the point form the shape of area that is closest to that point. Does this ring a bell to anyone? I've had a tough time googling descriptions and getting results. And I don't know how else to describe it. Hopefully the picture helps.










    share|cite|improve this question







    New contributor




    Brian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







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      1












      1








      1





      $begingroup$


      I encountered an algorithm to solve a real world problem, and I remember a class I took where I made something very similar for some for a homework problem. it looks like this



      Basically it's a plot of points, and the lines are drawn to be equidistant between two points. It forms a perfect partition where the lines around the point form the shape of area that is closest to that point. Does this ring a bell to anyone? I've had a tough time googling descriptions and getting results. And I don't know how else to describe it. Hopefully the picture helps.










      share|cite|improve this question







      New contributor




      Brian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I encountered an algorithm to solve a real world problem, and I remember a class I took where I made something very similar for some for a homework problem. it looks like this



      Basically it's a plot of points, and the lines are drawn to be equidistant between two points. It forms a perfect partition where the lines around the point form the shape of area that is closest to that point. Does this ring a bell to anyone? I've had a tough time googling descriptions and getting results. And I don't know how else to describe it. Hopefully the picture helps.







      algorithms






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      Brian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 2 hours ago









      BrianBrian

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          2 Answers
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          $begingroup$

          What you described is Voronoi diagram.



          Here is an excerpt from Wikipedia.




          Picture of Voronoi diagram from Wikipedia



          In the simplest case, shown in the first picture, we are given a finite set of points ${p_1, cdots, p_n}$ in the Euclidean plane. In this case each site $p_k$ is simply a point, and its corresponding Voronoi cell $R_k$ consists of every point in the Euclidean plane whose distance to $p_k$ is less than or equal to its distance to any other points. Each such cell is obtained from the intersection of half-spaces, and hence it is a convex polygon. The line segments of the Voronoi diagram are all the points in the plane that are equidistant to the two nearest sites. The Voronoi vertices (nodes) are the points equidistant to three (or more) sites.







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          • $begingroup$
            +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
            $endgroup$
            – Sagnik
            1 hour ago



















          -1












          $begingroup$

          You are looking for a Multi-Class Classification Algorithm. I suggest you have a look at:




          • K-Nearest Neighbors algorithm (or KNN). Here is an introductory blog post.

          • Support Vector Machines. You can start reading up on it here.






          share|cite|improve this answer









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            2 Answers
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            active

            oldest

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            2 Answers
            2






            active

            oldest

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            active

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            active

            oldest

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            3












            $begingroup$

            What you described is Voronoi diagram.



            Here is an excerpt from Wikipedia.




            Picture of Voronoi diagram from Wikipedia



            In the simplest case, shown in the first picture, we are given a finite set of points ${p_1, cdots, p_n}$ in the Euclidean plane. In this case each site $p_k$ is simply a point, and its corresponding Voronoi cell $R_k$ consists of every point in the Euclidean plane whose distance to $p_k$ is less than or equal to its distance to any other points. Each such cell is obtained from the intersection of half-spaces, and hence it is a convex polygon. The line segments of the Voronoi diagram are all the points in the plane that are equidistant to the two nearest sites. The Voronoi vertices (nodes) are the points equidistant to three (or more) sites.







            share|cite|improve this answer









            $endgroup$













            • $begingroup$
              +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
              $endgroup$
              – Sagnik
              1 hour ago
















            3












            $begingroup$

            What you described is Voronoi diagram.



            Here is an excerpt from Wikipedia.




            Picture of Voronoi diagram from Wikipedia



            In the simplest case, shown in the first picture, we are given a finite set of points ${p_1, cdots, p_n}$ in the Euclidean plane. In this case each site $p_k$ is simply a point, and its corresponding Voronoi cell $R_k$ consists of every point in the Euclidean plane whose distance to $p_k$ is less than or equal to its distance to any other points. Each such cell is obtained from the intersection of half-spaces, and hence it is a convex polygon. The line segments of the Voronoi diagram are all the points in the plane that are equidistant to the two nearest sites. The Voronoi vertices (nodes) are the points equidistant to three (or more) sites.







            share|cite|improve this answer









            $endgroup$













            • $begingroup$
              +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
              $endgroup$
              – Sagnik
              1 hour ago














            3












            3








            3





            $begingroup$

            What you described is Voronoi diagram.



            Here is an excerpt from Wikipedia.




            Picture of Voronoi diagram from Wikipedia



            In the simplest case, shown in the first picture, we are given a finite set of points ${p_1, cdots, p_n}$ in the Euclidean plane. In this case each site $p_k$ is simply a point, and its corresponding Voronoi cell $R_k$ consists of every point in the Euclidean plane whose distance to $p_k$ is less than or equal to its distance to any other points. Each such cell is obtained from the intersection of half-spaces, and hence it is a convex polygon. The line segments of the Voronoi diagram are all the points in the plane that are equidistant to the two nearest sites. The Voronoi vertices (nodes) are the points equidistant to three (or more) sites.







            share|cite|improve this answer









            $endgroup$



            What you described is Voronoi diagram.



            Here is an excerpt from Wikipedia.




            Picture of Voronoi diagram from Wikipedia



            In the simplest case, shown in the first picture, we are given a finite set of points ${p_1, cdots, p_n}$ in the Euclidean plane. In this case each site $p_k$ is simply a point, and its corresponding Voronoi cell $R_k$ consists of every point in the Euclidean plane whose distance to $p_k$ is less than or equal to its distance to any other points. Each such cell is obtained from the intersection of half-spaces, and hence it is a convex polygon. The line segments of the Voronoi diagram are all the points in the plane that are equidistant to the two nearest sites. The Voronoi vertices (nodes) are the points equidistant to three (or more) sites.








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            answered 1 hour ago









            Apass.JackApass.Jack

            8,6451634




            8,6451634












            • $begingroup$
              +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
              $endgroup$
              – Sagnik
              1 hour ago


















            • $begingroup$
              +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
              $endgroup$
              – Sagnik
              1 hour ago
















            $begingroup$
            +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
            $endgroup$
            – Sagnik
            1 hour ago




            $begingroup$
            +1. I refrained from mentioning them and went for implementations because I remember my professors mentioning them with a footnote that Voronoi Diagrams are computationally quite complex to implement in higher dimensions. So simple kNN implementations get the job done much better. However the condition that "lines are drawn to be equidistant between two points" may not be fulfilled.
            $endgroup$
            – Sagnik
            1 hour ago











            -1












            $begingroup$

            You are looking for a Multi-Class Classification Algorithm. I suggest you have a look at:




            • K-Nearest Neighbors algorithm (or KNN). Here is an introductory blog post.

            • Support Vector Machines. You can start reading up on it here.






            share|cite|improve this answer









            $endgroup$


















              -1












              $begingroup$

              You are looking for a Multi-Class Classification Algorithm. I suggest you have a look at:




              • K-Nearest Neighbors algorithm (or KNN). Here is an introductory blog post.

              • Support Vector Machines. You can start reading up on it here.






              share|cite|improve this answer









              $endgroup$
















                -1












                -1








                -1





                $begingroup$

                You are looking for a Multi-Class Classification Algorithm. I suggest you have a look at:




                • K-Nearest Neighbors algorithm (or KNN). Here is an introductory blog post.

                • Support Vector Machines. You can start reading up on it here.






                share|cite|improve this answer









                $endgroup$



                You are looking for a Multi-Class Classification Algorithm. I suggest you have a look at:




                • K-Nearest Neighbors algorithm (or KNN). Here is an introductory blog post.

                • Support Vector Machines. You can start reading up on it here.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered 2 hours ago









                SagnikSagnik

                584319




                584319






















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