Closed patrickkostjens closed 8 years ago
Merging #24 into master will increase coverage by +<.01%
- 2 files (not in diff) in
.../de/lmu/ifi/dbs/elki
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I think this could be modified to use PrototypeModel
instead of MeanModel
(to allow PAM etc. instead of k-means; and arbitrary distance functions), or it should allow NumberVectorDistanceFunction
only instead of arbitary distances.
@since
should be added when preparing a new release, on everything new in that release. @Alias
is for backwards compatibility with old class names, so this is also not needed on new functionality.
clusterBoundary
should probably be a int
.
But this looks pretty good, I will merge it when I have time (I'm busy with other projects right now, sorry)
I incorporated all except your first comment since I am not entirely sure how to make the modifications for that one. I agree with you that it would be better to use PrototypeModel
instead of MeanModel
. However, the PrototypeModel
requires a type paramater that is different from the type paramater of the database and the CBLOF algorithm as it currently is. To be able to use the distance function of the database, the type of the PrototypeModel
has to match that of the DistanceQuery
, but I do not think that is possible since that is fixed to be the same as the database and algorithm parameter.
I hope this makes sense, but what I think it comes down to is that I do not know a way to perform distance queries on an arbitrary output type returned as the prototype by PrototypeModel
.
Merged in 512af8454e031339eee04193c6ab0b4769203bb3, thank you!
This is my implementation of the CBLOF algorithm by He et al. I used the LOF and KMeansOutlier algorithms as the main examples for the implementation. Furthermore, I put 0.7.2 as the
@since
version in the comments, but I am unsure whether that version is correct.