Algorithm Capability

AKA: Algorithm Characteristic, Algorithm Property, Algorithm Feature.
- …
Example(s):
- its low Computational Complexity.
- its low Resource Complexity.
- its adaptability to new Tasks.
See: Person Capability, Business Process Capability.

References

(Chen et al., 2009) ⇒ Bo Chen, Wai Lam, Ivor Tsang, and Tak-Lam Wong. (2009). “Extracting Discrimininative Concepts for Domain Adaptation in Text Mining.” In: Proceedings of ACM SIGKDD Conference (KDD-2009). doi:10.1145/1557019.1557045
- Another characteristic of our method is its capability for considering multiple classes and their interactions simultaneously.

(Brohée & van Helden, 2006) ⇒ Sylvain Brohée and Jacques van Helden. (2006). “Evaluation of clustering algorithms for protein-protein interaction networks.” In: BMC bioinformatics.
- In this paper we present a systematic quantitative evaluation of the capability of four clustering methods for inferring protein complexes from a network of pairwise protein interactions.
- Note that this removal experiment is not very indicative of algorithm capability under realistic conditions, because the partitioning of the test graph corresponds almost with complex composition
- The next step was to evaluate the capability of these algorithms to extract relevant information from high-throughput data sets.
- This reflects the fact that this algorithm has the capability to discard nodes from the clustering result (unassigned nodes).

(Fogel & al) ⇒ David B. Fogel, Thomas Bäck, and Zbigniew Michalewicz. (2000). “Evolutionary Computation: Basic algorithms and operators.” CRC Press
- Convergence reliability: Informally, the convergence reliability of an evolutionary algorithm means its capability to yield reasonable good solution in the case of highly multimodal topologies of the objective function.