Predicting Fashion using Machine Learning techniques
Year: 2017
Type: dissertation
Abstract: On a high-level perspective, fashion is an art defined by fash- ion stylists and designers to express their thoughts and opinions. Lately, fashion have also been defined by digital publishers such as bloggers and online magazines. These digital publishers create fashion by curating and publishing content that is hopefully rel- evant and of high quality for their readers. Within this master’s thesis, fashion forecasting was investigated by applying supervised machine learning techniques. The problem was investigated by training classification learning models on a real world historical fashion dataset. The investigation has shown promising results, where fashion forecasting has been achieved with an average ac- curacy above 65 % .
Author: Mona Dadoun
Language: English
Subfield: Visual Arts and Performing Arts
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2767392160