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VC dimension of hypothesis space of finite union of intervals



2019 Community Moderator ElectionRelationship between VC dimension and degrees of freedomHow to set weight in Weighted Kernel K-Means?How to calculate VC-dimension?Generalization Error DefinitionHow to determine the VC Dimension of axis-aligned, origin-centered ellipses?Dimension problem in keras neural networksWhat is the exact definition of VC dimension?Why the VC dimension to this linear hypothesis equal to 3?Mapping between original feature space and an interpretable feature spacePossible Growth Function for a hypothesis set










3












$begingroup$


I have the following concept:
$$C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,kright
$$

and was wondering how to determine the VC dimension of C?










share|improve this question











$endgroup$
















    3












    $begingroup$


    I have the following concept:
    $$C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,kright
    $$

    and was wondering how to determine the VC dimension of C?










    share|improve this question











    $endgroup$














      3












      3








      3





      $begingroup$


      I have the following concept:
      $$C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,kright
      $$

      and was wondering how to determine the VC dimension of C?










      share|improve this question











      $endgroup$




      I have the following concept:
      $$C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,kright
      $$

      and was wondering how to determine the VC dimension of C?







      machine-learning classification vc-theory






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 28 at 12:46









      Esmailian

      2,639318




      2,639318










      asked Mar 27 at 13:15









      globetroterglobetroter

      182




      182




















          1 Answer
          1






          active

          oldest

          votes


















          0












          $begingroup$

          VC dimension is defined for a hypothesis space $H$, e.g. a set of binary classifiers $C rightarrow 0, 1$. For example, hypothesis space
          $$H=Bbb 1_x le theta: theta in Bbb R$$
          has VC dimension $1$, because for $C=23, 56$, it does not contain a classifier that gives $23 rightarrow 0, 56 rightarrow 1$.



          For example, a classifier from $H$ would be $f(x)=Bbb 1_x le 40$ that gives $23 rightarrow 1, 56 rightarrow 0$.



          From C to H



          As you have illustrated in the comments, we can build a hypothesis space $H$ from $C$ as follows:
          $$H=leftBbb 1_x in C: C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,krightright$$
          Meaning, each classifier in $H$ is a union of $k$ intervals that labels a point inside the union as $1$ and outside as $0$.



          VC dimension of this $H$ is $2k$:



          1. For VC $geq 2k$: Let $A$ be an arbitrary set , and $A rightarrow 0, 1$ be an arbitrary labeling. By going from minimum to maximum member of $A$, we can cover all adjacent $1$s with one interval, and only need to use another interval when there is a $0$ barrier. Therefore, we need $k$ intervals to cover $k$ isolated regions of $1$s. Furthermore, a set with $2k$ members has at most $k$ isolated $1$s (since to have $k+1$ isolated $1$s there should be $k$ $0$ barriers in-between), and thus, needs at most $k$ intervals.


          2. For VC $< 2k+1$ by contradiction: ordered set $A_2k+1=a_1<...<a_2k+1$, with labeling $a_k rightarrow 1_textk odd$, i.e. $a_1 rightarrow 1, a_2 rightarrow 0,...,a_2k+1 rightarrow 1$, has $k+1$ isolated $1$s which cannot be covered with $k$ intervals.






          share|improve this answer











          $endgroup$












          • $begingroup$
            Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
            $endgroup$
            – globetroter
            Mar 28 at 5:55










          • $begingroup$
            @LarsErik That works! Updated.
            $endgroup$
            – Esmailian
            Mar 28 at 10:54











          Your Answer





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          1 Answer
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          1 Answer
          1






          active

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          active

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          active

          oldest

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          0












          $begingroup$

          VC dimension is defined for a hypothesis space $H$, e.g. a set of binary classifiers $C rightarrow 0, 1$. For example, hypothesis space
          $$H=Bbb 1_x le theta: theta in Bbb R$$
          has VC dimension $1$, because for $C=23, 56$, it does not contain a classifier that gives $23 rightarrow 0, 56 rightarrow 1$.



          For example, a classifier from $H$ would be $f(x)=Bbb 1_x le 40$ that gives $23 rightarrow 1, 56 rightarrow 0$.



          From C to H



          As you have illustrated in the comments, we can build a hypothesis space $H$ from $C$ as follows:
          $$H=leftBbb 1_x in C: C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,krightright$$
          Meaning, each classifier in $H$ is a union of $k$ intervals that labels a point inside the union as $1$ and outside as $0$.



          VC dimension of this $H$ is $2k$:



          1. For VC $geq 2k$: Let $A$ be an arbitrary set , and $A rightarrow 0, 1$ be an arbitrary labeling. By going from minimum to maximum member of $A$, we can cover all adjacent $1$s with one interval, and only need to use another interval when there is a $0$ barrier. Therefore, we need $k$ intervals to cover $k$ isolated regions of $1$s. Furthermore, a set with $2k$ members has at most $k$ isolated $1$s (since to have $k+1$ isolated $1$s there should be $k$ $0$ barriers in-between), and thus, needs at most $k$ intervals.


          2. For VC $< 2k+1$ by contradiction: ordered set $A_2k+1=a_1<...<a_2k+1$, with labeling $a_k rightarrow 1_textk odd$, i.e. $a_1 rightarrow 1, a_2 rightarrow 0,...,a_2k+1 rightarrow 1$, has $k+1$ isolated $1$s which cannot be covered with $k$ intervals.






          share|improve this answer











          $endgroup$












          • $begingroup$
            Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
            $endgroup$
            – globetroter
            Mar 28 at 5:55










          • $begingroup$
            @LarsErik That works! Updated.
            $endgroup$
            – Esmailian
            Mar 28 at 10:54















          0












          $begingroup$

          VC dimension is defined for a hypothesis space $H$, e.g. a set of binary classifiers $C rightarrow 0, 1$. For example, hypothesis space
          $$H=Bbb 1_x le theta: theta in Bbb R$$
          has VC dimension $1$, because for $C=23, 56$, it does not contain a classifier that gives $23 rightarrow 0, 56 rightarrow 1$.



          For example, a classifier from $H$ would be $f(x)=Bbb 1_x le 40$ that gives $23 rightarrow 1, 56 rightarrow 0$.



          From C to H



          As you have illustrated in the comments, we can build a hypothesis space $H$ from $C$ as follows:
          $$H=leftBbb 1_x in C: C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,krightright$$
          Meaning, each classifier in $H$ is a union of $k$ intervals that labels a point inside the union as $1$ and outside as $0$.



          VC dimension of this $H$ is $2k$:



          1. For VC $geq 2k$: Let $A$ be an arbitrary set , and $A rightarrow 0, 1$ be an arbitrary labeling. By going from minimum to maximum member of $A$, we can cover all adjacent $1$s with one interval, and only need to use another interval when there is a $0$ barrier. Therefore, we need $k$ intervals to cover $k$ isolated regions of $1$s. Furthermore, a set with $2k$ members has at most $k$ isolated $1$s (since to have $k+1$ isolated $1$s there should be $k$ $0$ barriers in-between), and thus, needs at most $k$ intervals.


          2. For VC $< 2k+1$ by contradiction: ordered set $A_2k+1=a_1<...<a_2k+1$, with labeling $a_k rightarrow 1_textk odd$, i.e. $a_1 rightarrow 1, a_2 rightarrow 0,...,a_2k+1 rightarrow 1$, has $k+1$ isolated $1$s which cannot be covered with $k$ intervals.






          share|improve this answer











          $endgroup$












          • $begingroup$
            Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
            $endgroup$
            – globetroter
            Mar 28 at 5:55










          • $begingroup$
            @LarsErik That works! Updated.
            $endgroup$
            – Esmailian
            Mar 28 at 10:54













          0












          0








          0





          $begingroup$

          VC dimension is defined for a hypothesis space $H$, e.g. a set of binary classifiers $C rightarrow 0, 1$. For example, hypothesis space
          $$H=Bbb 1_x le theta: theta in Bbb R$$
          has VC dimension $1$, because for $C=23, 56$, it does not contain a classifier that gives $23 rightarrow 0, 56 rightarrow 1$.



          For example, a classifier from $H$ would be $f(x)=Bbb 1_x le 40$ that gives $23 rightarrow 1, 56 rightarrow 0$.



          From C to H



          As you have illustrated in the comments, we can build a hypothesis space $H$ from $C$ as follows:
          $$H=leftBbb 1_x in C: C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,krightright$$
          Meaning, each classifier in $H$ is a union of $k$ intervals that labels a point inside the union as $1$ and outside as $0$.



          VC dimension of this $H$ is $2k$:



          1. For VC $geq 2k$: Let $A$ be an arbitrary set , and $A rightarrow 0, 1$ be an arbitrary labeling. By going from minimum to maximum member of $A$, we can cover all adjacent $1$s with one interval, and only need to use another interval when there is a $0$ barrier. Therefore, we need $k$ intervals to cover $k$ isolated regions of $1$s. Furthermore, a set with $2k$ members has at most $k$ isolated $1$s (since to have $k+1$ isolated $1$s there should be $k$ $0$ barriers in-between), and thus, needs at most $k$ intervals.


          2. For VC $< 2k+1$ by contradiction: ordered set $A_2k+1=a_1<...<a_2k+1$, with labeling $a_k rightarrow 1_textk odd$, i.e. $a_1 rightarrow 1, a_2 rightarrow 0,...,a_2k+1 rightarrow 1$, has $k+1$ isolated $1$s which cannot be covered with $k$ intervals.






          share|improve this answer











          $endgroup$



          VC dimension is defined for a hypothesis space $H$, e.g. a set of binary classifiers $C rightarrow 0, 1$. For example, hypothesis space
          $$H=Bbb 1_x le theta: theta in Bbb R$$
          has VC dimension $1$, because for $C=23, 56$, it does not contain a classifier that gives $23 rightarrow 0, 56 rightarrow 1$.



          For example, a classifier from $H$ would be $f(x)=Bbb 1_x le 40$ that gives $23 rightarrow 1, 56 rightarrow 0$.



          From C to H



          As you have illustrated in the comments, we can build a hypothesis space $H$ from $C$ as follows:
          $$H=leftBbb 1_x in C: C = leftbigcup_i=1^k(a_i, b_i): a_i, b_i in Bbb R, a_i < b_i, i=1,2,..,krightright$$
          Meaning, each classifier in $H$ is a union of $k$ intervals that labels a point inside the union as $1$ and outside as $0$.



          VC dimension of this $H$ is $2k$:



          1. For VC $geq 2k$: Let $A$ be an arbitrary set , and $A rightarrow 0, 1$ be an arbitrary labeling. By going from minimum to maximum member of $A$, we can cover all adjacent $1$s with one interval, and only need to use another interval when there is a $0$ barrier. Therefore, we need $k$ intervals to cover $k$ isolated regions of $1$s. Furthermore, a set with $2k$ members has at most $k$ isolated $1$s (since to have $k+1$ isolated $1$s there should be $k$ $0$ barriers in-between), and thus, needs at most $k$ intervals.


          2. For VC $< 2k+1$ by contradiction: ordered set $A_2k+1=a_1<...<a_2k+1$, with labeling $a_k rightarrow 1_textk odd$, i.e. $a_1 rightarrow 1, a_2 rightarrow 0,...,a_2k+1 rightarrow 1$, has $k+1$ isolated $1$s which cannot be covered with $k$ intervals.







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Mar 28 at 12:48

























          answered Mar 27 at 14:41









          EsmailianEsmailian

          2,639318




          2,639318











          • $begingroup$
            Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
            $endgroup$
            – globetroter
            Mar 28 at 5:55










          • $begingroup$
            @LarsErik That works! Updated.
            $endgroup$
            – Esmailian
            Mar 28 at 10:54
















          • $begingroup$
            Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
            $endgroup$
            – globetroter
            Mar 28 at 5:55










          • $begingroup$
            @LarsErik That works! Updated.
            $endgroup$
            – Esmailian
            Mar 28 at 10:54















          $begingroup$
          Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
          $endgroup$
          – globetroter
          Mar 28 at 5:55




          $begingroup$
          Hi, thanks for the response. It turns out the problem C is actually the hypothesis set. You can label an arbitrary number x using C in the following way: if x is in some interval, say, (a_i, b_i) in C, its label is 1, otherwise, its label is -1.More concisely, only the number in the union of k intervals would be labeled 1.
          $endgroup$
          – globetroter
          Mar 28 at 5:55












          $begingroup$
          @LarsErik That works! Updated.
          $endgroup$
          – Esmailian
          Mar 28 at 10:54




          $begingroup$
          @LarsErik That works! Updated.
          $endgroup$
          – Esmailian
          Mar 28 at 10:54

















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