03345ntm a22005417i 4500 000722931 CZ-PrVSE 20260201122909.0 m d cr n|||||||||| 260201s2025 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Landsmann, Jiří ISIS:173073 dis Aproximace agregovaných dat na nižší úrovně eng Approximation of measures to lower granularities / Jiří Landsmann 2025 ?? stran : digital, PDF soubor Vedoucí práce: Petr Máša Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2026 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2026 Disaggregating socio-economic indicators from coarse regional aggregates to finer spatial units is a recurring challenge in public policy and statistical analysis. While traditional methods such as areal interpolation and regression assume full supervision or spatial continuity, they fall short when fine-grained ground truth is unavailable. This thesis proposes a modular, simulation-based pipeline for approximating fine-resolution values from coarse inputs using auxiliary features. The method combines unsupervised clustering, simulation of district-level targets consistent with known regional aggregates, and supervised learning on the synthetic data. It is designed to generalize across different indicators and domains. The pipeline is evaluated on two tasks: unemployment prediction and education level estimation at the district level in the Czech Republic. Using voting data and household structure as auxiliary inputs, the method consistently outperforms strong baselines and reproduces intra-regional variation more faithfully than models trained directly on coarse labels. The results demonstrate that meaningful disaggregation is possible even under partial supervision, offering a scalable solution for real-world deployment in data-scarce environments. Způsob přístupu: Internet znalostní a webové technologie [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas data disaggregation machine learning unemployment simulation clustering education level Máša, Petr ISIS:17194 ths Bakuncová, Karolína ISIS:149295 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/87868/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/87868 Hlavní práce https://insis.vse.cz/zp/87868/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/87868/posudek/oponent/86623 Oponentura https://insis.vse.cz/zp/87868/priloha/32856 Přiloha k práci https://insis.vse.cz/zp/87868/podrobnosti dc:identifier NEPOSILAT VSKP vse87868 260121 87868