The Evolving Tree--analysis and applications.
In this paper, we enhance and analyze the Evolving Tree (ETree) data analysis algorithm. The suggested improvements aim to make the system perform better while still maintaining the simple nature of the basic algorithm. We also examine the system's behavior with many different kinds of tests, measurements and visualizations. We compare the ETree's performance against classical data analysis methods and very similar modern systems. We find that the ETree is a suitable method for unsupervised analysis of huge data sets.
Pakkanen
Jussi
J
Neural Networks Research Centre, Helsinki University of Technology, Helsinki 02015 HUT, Finland. jussi.pakkanen@hut.fi
Iivarinen
Jukka
J
Oja
Erkki
E
D000465:Algorithms; D001185:Artificial Intelligence; D016247:Information Storage and Retrieval / Q000379:methods*; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D013598:Systems Theory