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A novice here

My previous question was closed due to inadequate details

So here I've added more details

A metric should basically satisfy 3 properties

  1. Distance is equal to zero if and only if $x$ is equal to $y$ ($d(x,y)=0 ⇔ x=y$))
  2. Distance from $x$ to $y$ is the same as distance from $y$ to $x$ ($d(x,y)=d(y,x)$)
  3. Distance should satisfy the triangular inequality ($d(x,y)\leq d(x,z) +d(z,y)$)

I already know that Gower's distance satisfy the first 2 properties to be a metric, but I want to know whether it satisfies the triangular inequality property.

The reason I want to know this, is because all metric spaces are Hausdorff spaces, and I want use the Gowers distance in order to find the Hausdorff distance for 2 sets of points.

In my case, a point contains data of mixed types (logical, categorical & numeral), and therefore I have to use the Gowers distance.

Any help would be appreciated.

Thank You!

Edit:

According to a suggestion on the comments, here is the formal definition of a metric

A metric on a set X is a function (called the distance function or simply distance)

$d : X × X → R$

(where R is the set of real numbers). For all $ x, y, z $ in $X$, this function is required to satisfy the following conditions:

  1. $d(x, y) ≥ 0$ (non-negativity)
  2. $d(x, y) = 0$ if and only if $x = y $
  3. $d(x, y) = d(y, x) $ (symmetry)
  4. $d(x, z) ≤ d(x, y) + d(y, z) $

Note that the first condition is implied by the others.

1 Answers1

1

Referring to the answer in https://stats.stackexchange.com/questions/15287/hierarchical-clustering-with-mixed-type-data-what-distance-similarity-to-use

"Gower distance". Without ordinal variables present (i.e. w/o using the Podani's option) $\sqrt{1-GS}$ behaves as Euclidean distance, it fully supports euclidean space. But $1-GS$ is only a metric (supports triangular inequality), not Euclidean. With ordinal variables present (using the Podani's option) $\sqrt{1-GS}$ is only a metric, not Euclidean; and $1-GS$ isn't a metric at all. See also.

Therefore it can be used a metric


Papers

1 Gower J. C. A general coefficient of similarity and some of its properties // Biometrics, 1971, 27, 857-872

2 Podani, J. Extending Gower’s general coefficient of similarity to ordinal characters // Taxon, 1999, 48, 331-340

Henry
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