[ https://issues.apache.org/jira/browse/MATH1367?page=com.atlassian.jira.plugin.system.issuetabpanels:alltabpanel
]
Amol Singh updated MATH1367:

Description:
The DSCAN paper describes the epsneighborhood of a point as
https://www.aaai.org/Papers/KDD/1996/KDD96037.pdf (Page 2)
Definition 1: (Epsneighborhood of a point) The Epsneighborhood of a point p, denoted by
NEps(p), is defined by NEps(p) = {q ∈ D  dist(p,q)< Eps}
in other words for all q points that are a member of database D whose distance from p is less
that Eps should be classified as a neighbor. This should include the point itself.
The implementation however has a reference check to the point itself and does not add it to
its neighbors list.
private List<T> getNeighbors(final T point, final Collection<T> points) {
final List<T> neighbors = new ArrayList<T>();
for (final T neighbor : points) {
if (point != neighbor && distance(neighbor, point) <= eps) {
neighbors.add(neighbor);
}
}
return neighbors;
}
"point != neighbor " check should be removed here. Keeping this check effectively is raising
the minPts count by 1. Other third party QuadTree backed DBSCAN implementations consider the
center point in its neighbor count E.g. bmwcarit library.
If this is infact by design, the check should use value equality instead of reference equality.
T extends Clusterable<T> , the client should be able to define this behavior.
was:
The DSCAN paper describes the epsneighborhood of a point as
https://www.aaai.org/Papers/KDD/1996/KDD96037.pdf (Page 2)
Definition 1: (Epsneighborhood of a point) The Epsneighborhood of a point p, denoted by
NEps(p), is defined by NEps(p) = {q ∈ D  dist(p,q)< Eps}
in other words for all q points that are a member of database D whose distance from p is less
that Eps should be classified as a neighbor. This should include the point itself.
The implementation however has a reference check to the point itself and does not add it to
its neighbors list.
private List<T> getNeighbors(final T point, final Collection<T> points) {
final List<T> neighbors = new ArrayList<T>();
for (final T neighbor : points) {
if (point != neighbor && distance(neighbor, point) <= eps) {
neighbors.add(neighbor);
}
}
return neighbors;
}
"point != neighbor " check should be removed here. Shouldn't the cluster include the point
itself in it? Keeping this check effectively is raising the minPts count by 1. Other third
party QuadTree backed DBSCAN implementations consider the center point in its neighbor count
E.g. bmwcarit library.
If this is infact by design, the check should use value equality instead of reference equality.
T extends Clusterable<T> , the client should be able to define this behavior.
> DBSCAN Implementation does not count the seed point itself as part of its neighbors count
> 
>
> Key: MATH1367
> URL: https://issues.apache.org/jira/browse/MATH1367
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 3.6.1
> Reporter: Amol Singh
> Fix For: 4.0
>
>
> The DSCAN paper describes the epsneighborhood of a point as
> https://www.aaai.org/Papers/KDD/1996/KDD96037.pdf (Page 2)
> Definition 1: (Epsneighborhood of a point) The Epsneighborhood of a point p, denoted
by NEps(p), is defined by NEps(p) = {q ∈ D  dist(p,q)< Eps}
> in other words for all q points that are a member of database D whose distance from p
is less that Eps should be classified as a neighbor. This should include the point itself.
> The implementation however has a reference check to the point itself and does not add
it to its neighbors list.
> private List<T> getNeighbors(final T point, final Collection<T> points) {
> final List<T> neighbors = new ArrayList<T>();
> for (final T neighbor : points) {
> if (point != neighbor && distance(neighbor, point) <= eps) {
> neighbors.add(neighbor);
> }
> }
> return neighbors;
> }
> "point != neighbor " check should be removed here. Keeping this check effectively is
raising the minPts count by 1. Other third party QuadTree backed DBSCAN implementations consider
the center point in its neighbor count E.g. bmwcarit library.
> If this is infact by design, the check should use value equality instead of reference
equality. T extends Clusterable<T> , the client should be able to define this behavior.

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