Predviđanje plaća zaposlenika temeljem podataka koristeći metode strojnog učenja

undergraduate thesis

• Title (english): Predicting employee salaries based on data using machine learning methods
• Author: Nataša Grgić
• Mentor: Tomislav Stipančić (mentor)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2024-02-28, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering

Abstract

Ovaj rad ima za cilj izgradnju modela predviđanja plaće zaposlenika koristeći odabrane ključne karakteristike i algoritme strojnog učenja. U području strojnog učenja koristi se tehnologija koja se oslanja na softverske programe, u ovom slučaju Python, kako bi postigla preciznije predviđanje ili detekciju te razvija računalne programe koji mogu koristiti podatke za autonomno učenje. Ovaj rad koristi klasifikacijske metode kao što su decision trees, random forest i linear regression. Također, provodi se usporedba različitih klasifikacijskih metoda kako bismo dobili uvid u to koja od njih pruža optimalno rješenje za postavljeni problem.

Abstract (english)

This paper aims to build a salary prediction model for employees using selected key features and machine learning algorithms. In the field of machine learning, the technology relies on software programs, in this case, Python, to achieve more accurate prediction or detection and develops computer programs that can use data for autonomous learning. This paper utilizes classification methods such as decision trees, random forest, and linear regression. Additionally, a comparison of different classification methods is conducted to gain insight into which one provides the optimal solution for the given problem.

• Keywords: strojno učenje; algoritam; Python; model predviđanja; klasifikacija; plaća
• Keywords (english): machine learning; algorithm; Python; prediction model; classification; salary
• Language: croatian
• URN:NBN: urn:nbn:hr:235:777498
• Study programme: Title: Mechanical Engineering; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-02-25 15:57:46