Korištenje metoda strojnog učenja u antropološkoj problematici (CROSBI ID 400345)
Ocjenski rad | diplomski rad
Podaci o odgovornosti
Carić, Tonko
Mateljan, Vladimir ; Sindik, Joško
hrvatski
Korištenje metoda strojnog učenja u antropološkoj problematici
Machine learning is a part of the field of computer science known as artificial intelligence that deals with the construction and analysing of systems that can learn from the data. The application of machine learning techniques in the analysis of large data sets is called data mining. In-depth analysis of data and its use in the detection of knowledge is an indispensable part of modern data analysis in scientific research, applied in many fields of science. Anthropology as interdisciplinary science in their research provides a broad space for the application of data mining, whose advantages and disadvantages, should be considered. The aim of this work was to review a few selected machine learning algorithms and to examine their use on real-world data set. Supervised and unsupervised learning was tested, with in depth analysis of decision tree algorithm (J48 classification techniques) and Naive Bayes classifier, which were used for prediction of diabetes mellitus from the PIMA Indian diabetes dataset made available by National Institute of Diabetes and Digestive and Kidney Diseases. For the processing of data and for descriptive statistics were used languages „R“ and "Python“, while machine learning algorithms were implemented in tool WEKA.
strojno učenje; dubinska analiza podataka; stabla odlučivanja; Bayes; antropologija
nije evidentirano
engleski
Using machine learning methods in the field of anthropology
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machine learning; data mining; decision trees; Bayes; anthropology
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Podaci o izdanju
72
25.09.2015.
obranjeno
Podaci o ustanovi koja je dodijelila akademski stupanj
Filozofski fakultet u Zagrebu
Zagreb