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undergraduate thesis
ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2019. urn:nbn:hr:200:526137
Lazor, Denis
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Institutional repository: Faculty of Electrical Engineering, Computer Science and Information Technology Osijek

Cite this document

Lazor, D. (2019). ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:526137

Lazor, Denis. "ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2019. https://urn.nsk.hr/urn:nbn:hr:200:526137

Lazor, Denis. "ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2019. https://urn.nsk.hr/urn:nbn:hr:200:526137

Lazor, D. (2019). 'ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 21 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:526137

Lazor D. ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2019 [cited 2024 May 21] Available at: https://urn.nsk.hr/urn:nbn:hr:200:526137

D. Lazor, "ALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:200:526137

Metadata
TitleALGORITAM SLUČAJNIH ŠUMA U OPENCV BIBLIOTECI
Title (english)Random forest algorithm in OpenCV library
AuthorDenis Lazor
MentorDamir Filko (mentor)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Computer Engineering and Automation)
(Chair of Automation and Robotics)
Osijek
Defense date and country2019-09-26, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
U ovom radu je obrađena teorijska podloga algoritma slučajnih šuma i njegova implementacija u OpenCV biblioteci. Primjena teorijske podloge je prikazana na primjeru klasifikacije stanica tumora dojke. U tu svrhu, uz ostale pomoćne biblioteke, korištena je OpenCV biblioteka te Python programski jezik i UCIML baza podataka. Nakon kreiranja slučajne šume i postavljanja njenih parametara sljedeći korak je bio učenje. Učenje je provedeno na 455 uzoraka gdje je svako stablo odluke unutra slučajne šume učeno koristeći nasumično odabran podskup uzoraka. Testiranje je provedeno na skupu od 114 uzoraka s maksimalnom preciznošću od 113 uspješnih klasifikacija i minimalnom preciznošću od 105 uspješnih klasifikacije ovisno o nasumično odabranom podskupu uzoraka.
Abstract (english)
In this paper the theoretical background of the random forest algorithm and its implementation in OpenCV library was elaborated. Application of the theoretical background was presented on the example of breast tumor cells classification. In addition to other support libraries, the OpenCV library was used with the Python programming language, and the UCIML database. After a random forest object was created and its parameters were set, the next step was learning. Learning was carried out on 455 samples where each decision tree inside a random forest was taught using a randomly selected subset of samples. Testing was performed on a set of 114 samples with a maximum precision of 113 successful classifications and a minimum precision of 105 successful classifications depending on a randomly selected subset of samples.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:526137
Study programmeTitle: Undergraduate University Study Programme
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-10-31 11:19:02