Inhaltszusammenfassung

structural fragments and support vector machines. it is tailored for bio-chemical databases, where the examples are 2-d descriptions of chemical compounds. the fragment generator finds all fragments (i.e., linearly connected atoms) that satisfy userspecified constraints regarding their frequency and generality. in this paper, we are querying for fragments within a minimum and a maximum frequency in the dataset. after fragment generation, we propose to apply support vector machines to the prob...structural fragments and support vector machines. it is tailored for bio-chemical databases, where the examples are 2-d descriptions of chemical compounds. the fragment generator finds all fragments (i.e., linearly connected atoms) that satisfy userspecified constraints regarding their frequency and generality. in this paper, we are querying for fragments within a minimum and a maximum frequency in the dataset. after fragment generation, we propose to apply support vector machines to the problem of inducing sars from these fragments. we conjuncture that support vector machines are particularly useful in this context, as they can deal with a large number of features. experiments in the domains of carcinogenicity and mutagenicity prediction show that minimum and maximum frequency queries for fragments can be answered within a reasonable time, and that the predictive accuracy obtained using these fragments is satisfactory. however, further experiments will have to confirm that this is a viable approach to inducing sars.},» weiterlesen» einklappen

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Klassifikation

DFG Fachgebiet:
4.43 - Informatik

DDC Sachgruppe:
Informatik