How to do … in ELKI
- Invoke ELKI from within Java
- Use index structures for accelerating data mining algorithms
- Process geo data in ELKI
- Perform geo-spatial outlier detection with an external neighborhood specification
- Precompute distance matrixes and use external distances
- Using sparse vector data
- more to come
See also the Tutorial section:
- Implementing a custom distance function, a variable exponent Minkowski-norm
- Implementing a new outlier detection algorithm, using the distances standard deviation
- Implementing a k-means clustering variant, producing clusters of the same size
Greedy outlier ensemble computes a large set of outlier detection methods, then constructs and evaluates a greedy ensemble based on these methods.
Cluster evaluation with segmented view detailes the configurations used for the ICDE 2012 demonstration on cluster evaluation.