2026-05-30T05:01:00.414Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:7035 2019-05-30T11:30:56Z 1

Machine learning techniques for inspection data analysis 2017 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/7035 Р. Булатовић З. Коњовић А. Ивић Đ. Obradović The unique data set was created by collecting data about sanitary inspection control on the territory of AP Vojvodina during the period of two years. The total number of multi-dimensional data records is 28,403. The Open Data with complete details is published on web site of Provincial Health Secretariat in the section Documents – Data, available for a bulk download. Data comprise temporal, spatial and categorical components and as such are highly suitable for a variety of analyses by means of machine learning techniques, especially neural networks. In this paper examples of linear regression and neural networks applications to analysis of the data are presented. The obtained results can be used for improving daily tasks like estimating inspection control workload, and alike. conferenceObject 453 458 7th International Conference on Information Society Technology and Management, ICIST 2017