Resumen

VITE CEVALLOS, Harry; CARVAJAL ROMERO, Héctor  y  BARREZUETA UNDA, Salomón. Application of automatic learning algorithms to classify the fertility of a banana soil. Conrado [online]. 2020, vol.16, n.72, pp. 15-19.  Epub 01-Feb-2020. ISSN 1990-8644.

The research focuses on describing how to integrate machine learning techniques into the management of the banana nutritional cycle. The type of research is correlating and descriptive, detailing the activities that must be carried out in order to articulate the use of automatic learning in the decision making of the banana producer, using supervised methods, techniques that allowed classifying the study data, selecting to the algorithm of Decision Trees, which correctly classified the information, facilitating the prediction of the behavior of soil nutrients, focusing the area that presented variations in nutrients, facilitating decision making to the banana producer and optimization of resources.

Palabras clave : Automatic learning, soil nutrients; decision making; precision agriculture.

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