CLUSTER ANALYSIS: A COMPREHENSIVE AND VERSATILE QGIS PLUGIN FOR PATTERN RECOGNITION IN GEOSPATIAL DATA

Abstract. As geospatial data continuously grows in complexity and size, the application of Machine Learning Data Mining techniques to analysis is increasingly essential solve real-world problems. Although last two decades, research this field produced innovative methodologies, they are usually applied specific situations not automatized for general use. Therefore, both generalization integration these methods with Geographic Information Systems (GIS) necessary support researchers organizations exploration, pattern recognition, prediction various applications data. In work, we present Cluster Analysis, a Python plugin that developed open-source software QGIS offers functionalities entire clustering process. Or tool provides different improvements from current solutions available QGIS, but also other widespread GIS software. The expanded features provided by allow users deal some most challenging problems data, such as high dimensional space, poor quality large size To highlight potential its limitations scenarios, development integrated considerable experimental phase natures granularities. Overall, shows good adequate flexibility plugin, outlines possibilities future developments can be community, given nature project.