Application of decision tree algorithms for discriminating among woody plant taxa based on the pollen season characteristics

Abstract

The aim of this study was to verify whether and which parameters of the atmospheric pollen season can distinguish between pollen types, the ranges of parameter values that delineate classes of taxa, and finally which taxa are similar to others within the domain of these parameter ranges. Decision tree algorithms were applied and the best tree was chosen to describe the rules of pollen classification. The study material consisted of airborne pollen grains of the following eight taxa: Alnus, Betula, Carpinus, Corylus, Cupressaceae, Fraxinus, Populus and Ulmus. Research was conducted in Lublin in eastern Poland during 2001-2013. The following six atmospheric pollen season parameters were analyzed: season start and end, duration, maximum daily pollen concentration, date of maximum pollen concentration, and the Seasonal Pollen Index (SPI). Four algorithms were used in data analysis and the J4.8 algorithm was chosen as the best for taxa classification, date of the end of season and the SPI value belonging to characteristics that served most to discriminate between pollen types. Based on the classification tree, the following four groups of taxa were identified: (i) Ulmus; (ii) Corylus, Alnus, Populus; (iii) Betula; and (iv) Carpinus, Fraxinus, Cupressaceae.

Keywords

• airborne pollen
• characteristics of pollen season
• decision tree
• J4.8 algorithm