Sökning: "Multi-label classification"

Visar resultat 11 - 15 av 28 uppsatser innehållade orden Multi-label classification.

1. 11. Evaluation of Active Learning Strategies for Multi-Label Text Classification

   Master-uppsats, Lunds universitet/Institutionen för datavetenskap

   Författare :Henric Zethraeus; Philip Horstmann; [2021]
   Nyckelord :Technology and Engineering;

   Sammanfattning : .... LÄS MER

3. 12. Text analysis for email multi label classification

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Kyriaki Paniskaki; Sanjit Harsha Kadam; [2020-07-08]
   Nyckelord :natural language processing; machine learning; multi label text classification; deep neural networks; bilingual texts; emails; short texts;

   Sammanfattning : This master’s thesis studies a multi label text classification task on a small data set of bilingual, English and Swedish, short texts (emails). Specifically, the size of the data set is 5800 emails and those emails are distributed among 107 classes with the special case that the majority of the emails includes the two languages at the same time. LÄS MER

4. 13. Test Case Generation from Specifications Using Natural Language Processing

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Alzahraa Salman; [2020]
   Nyckelord :Software testing; Test case generation; Natural Language Processing; Test case specifications; Programvarutestning; Testfallsgenerering; Naturlig språkbehandling; Testfallspecifikationer;

   Sammanfattning : Software testing plays a fundamental role in software engineering as it ensures the quality of a software system. However, one of the major challenges of software testing is its costs since it is a time and resource-consuming process which according to academia and industry can take up to 50% of the total development cost. LÄS MER

5. 14. Applying machine learning algorithms to multi-label text classification on GitHub issues

   Kandidat-uppsats, Högskolan i Halmstad

   Författare :Daniel Artmann; [2020]
   Nyckelord :;

   Sammanfattning : This report compares five machine learning algorithms in their ability to categorize code repositories. The focus of expanding software projects tend to shift from developing new software to the maintenance of the projects. Maintainers can label code repositories to organize the project, but this requires manual labor and time. LÄS MER

7. 15. Multi-Label Text Classification with Transfer Learning for Policy Documents : The Case of the Sustainable Development Goals

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Samuel Rodríguez Medina; [2019]
   Nyckelord :machine learning; deep neural networks; transfer learning; text classification; sustainable development goals; sdgs;

   Sammanfattning : We created and analyzed a text classification dataset from freely-available web documents from the United Nation's Sustainable Development Goals. We then used it to train and compare different multi-label text classifiers with the aim of exploring the alternatives for methods that facilitate the search of information of this type of documents. LÄS MER