Classification tree applying for automated CV filtering in transport company

Abstract The article describes a system that uses the WEKA (Waikato Environment for Knowledge Analysis) environment as the source of a trained decision tree. The resulting tree is then used to automate the primary classification of various data. Several examples of the application of the system are considered. When using automatic analysis of CVs (curriculum vitae) sent to a large transportation company, the initial automatic CV classification facilitates the work of the human resources department of the company. Also, the logistical task of "MoB" (Make or Buy) is considered. In this case, the presence of an automatic classifier allows the system to advise the operator the best way to deliver the goods. The article shows the structure of the created software prototype, as well as the flow charts of all the created key nodes; it describes the process of preparing data, setting up the tree, importing it from WEKA environment into Python code, visualization, using it to classify new data.