An Active Search Method for Finding Objects with Near-Optimal Property Values within a Given Set

作者：da Matta Claudia E; Paiva Henrique M; Galvao Roberto K H; Araujo Mario C U^*; Soares Sofacles F C; Weber Karen C; Pinto Luiz A

来源：Journal of the Brazilian Chemical Society, 2016, 27(7): 1177-1187.

DOI：10.5935/0103-5053.20160014

• optimization
• quantitative structure-activity relationship
• antidepressant compounds
• near-infrared spectrometry
• eucalyptus pulp yield

This paper proposes an active search method aimed at finding objects with optimal or nearoptimal y-property values, on the basis of x-variables obtained by indirect, less costly methods. The proposed method progresses in a sequential manner, starting from a small subset of objects with known y-values. At each iteration, the K-nearest neighbour regression technique is employed to obtain estimates y for the objects with unknown y-values. The object with best y value is then subjected to a direct analysis procedure for evaluation of the y-property. Examples are presented with simulated data, as well as actual quantitative structure-activity relationship (QSAR) and near-infrared (NIR) spectrometry datasets. The QSAR and NIR case studies involve the search for maximal antidepressant activity in a set of arylpiperazine compounds and maximal pulp yield in a set of eucalyptus wood samples, respectively. In all these cases, the active search yielded results closer to the maximal y-value compared to the classical Kennard-Stone algorithm for object selection.

• 出版日期2016-6