diplomsko delo
Natan Šemrl (Author), Martin Možina (Mentor)

Abstract

V diplomskem delu se soočamo z odkrivanjem najslabših podskupin v napovednem modelu redne prodaje sadja in zelenjave. Osnovna želja je, da bi lahko model izboljšali tako, da vidimo, kje naredi napako, nato pa lahko z analizo ugotovimo, zakaj je napaka nastala. Problem smo rešili z uvedbo samodejnega postopka, ki išče kritične podskupine, tako da pridobi podatke, jih prečisti in pripravi, nato pa z uporabo algoritma za odkrivanje najde nekaj podskupin, ki so problematične. Poleg tega je bil velik del reševanja tudi analiza posameznih primerov za izboljšavo postopka. Po implementaciji se postopek redno izvaja in uporablja za poslovne potrebe podjetja.

Keywords

napovedovanje povpraševanja;prodaja;časovne vrste;napovedni model;podatkovna analiza;odkrivanje podskupin;visokošolski strokovni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [N. Šemrl]
UDC: 004(043.2)
COBISS: 190817027 Link will open in a new window
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Downloads: 9
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Other data

Secondary language: English
Secondary title: Discovery of critical subgroups in demand forecasting
Secondary abstract: The thesis deals with finding the worst subgroups in the forecasts of a machine learning model for fruits and vegetables. The primary goal is the improvement of the model, by seeing where it made a mistake, then analyzing that mistake and attempting to learn why it happened. We solved the problem by defining a process that searches for critical subgroups, first gathering and preparing the data, then running an algorithm to find a few problematic subgroups. Beside that, another part of problem solving was analyzing the cases themselves, to further improve the process. After the implementation, the process runs weekly and is used for the business needs of the company.
Secondary keywords: demand forecasting;sales;time series;forecasting model;data analysis;subgroup discovery;computer science;diploma;Napovedovanje;Povpraševanje (ekonomija);Analiza časovnih vrst;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000470
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 42 str.
ID: 23215657