Effective feature construction by maximum common subgraph sampling

The standard approach to feature construction and predictive learning in molecular datasets is to employ computationally expensive graph mining techniques and to bias the feature search exploration using frequency or correlation measures. These features are then typically employed in predictive mode...

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Bibliographic Details
Published in:	Machine learning Vol. 83; no. 2; pp. 137 - 161
Main Authors:	Schietgat, Leander, Costa, Fabrizio, Ramon, Jan, De Raedt, Luc
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01-05-2011 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Computation Computer Science Construction Control Data mining Decision trees Graphs Mathematical models Mechatronics Mining Natural Language Processing (NLP) Robotics Sampling Searching Simulation and Modeling Structure-activity learning Subgraph mining Chemoinformatics Feature generation
Online Access:	Get full text
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