6533b86efe1ef96bd12cc175
RESEARCH PRODUCT
Scalable robust clustering method for large and sparse data
Joonas HämäläinenTommi KärkkäinenTuomo Rossisubject
datadatasetsklusterianalyysiclusteringdescription
Datasets for unsupervised clustering can be large and sparse, with significant portion of missing values. We present here a scalable version of a robust clustering method with the available data strategy. Moreprecisely, a general algorithm is described and the accuracy and scalability of a distributed implementation of the algorithm is tested. The obtained results allow us to conclude the viability of the proposed approach. peerReviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-01 |