A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks

نویسندگان

  • Alessio Micheli
  • Filippo Portera
  • Alessandro Sperduti
چکیده

We consider two different methods for QSAR/QSPR regression tasks: Recursive Neural Networks (RecNN) and a Support Vector Regression (SVR) machine using a Tree Kernel. Experimental results on two specific regression tasks involving alkanes and benzodiazepines are obtained for the two approaches.

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تاریخ انتشار 2004