ANáLISE DE DADOS DE FISIOLOGIA DE PLANTAS APOIADA POR TéCNICAS DE VISUALIZA O DE INFORMA ES

This paper presents an alternative proposal for the analysis of data from plant physiology, using as support, information visualization techniques. These techniques can generate visualizations directly from data of high dimensionality, which can help to understand the data and serve to support the identification of the most relevant attributes for the discrimination of species. The selection of the most important parameters is essential for the construction of a classification model, either using a Bayesian classifier or Artificial NeuralNetwork.