Titlebook: Discovery Science; 13th International C Bernhard Pfahringer,Geoff Holmes,Achim Hoffmann Conference proceedings 2010 Springer Berlin Heidelb

泛濫

言外之意

Integer Linear Programming Models for Constrained Clustering,t to most approaches to constrained clustering, we do not constrain the way observations can be grouped into clusters, but the way candidate clusters can be combined into suitable clusterings. The constraints may concern the type of clustering (e.g., complete clusterings, overlapping or encompassing

遺傳

Stress-Fracture

投射

Graph Classification Based on Optimizing Graph Spectra,vel graph kernel, called SPEC, based on graph spectra and the Interlace Theorem, as well as an algorithm, called OPTSPEC, to optimize the SPEC kernel used in an SVM for graph classification. The fundamental performance of the method is evaluated using artificial datasets, and its practicality confir

Little

Algorithm for Detecting Significant Locations from Raw GPS Data,nt locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Assuming that a location is significant if users spend a certain time around that area, most current algorithms compare spatial/temporal variables, such as stay duration and a roaming d

草率男

必死

Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle,rmally distributed clusters and a cluster with a uniform distribution in an axis-aligned rectangular box. The uniform component extends the practical usability of the model e.g. in the presence of noise, and using the MDL principle for the model selection makes comparing the quality of clusterings w

ALB

alcohol-abuse