Sökning: "Text classification"

Visar resultat 11 - 15 av 362 uppsatser innehållade orden Text classification.

  1. 11. Speech Classification using Acoustic embedding and Large Language Models Applied on Alzheimer’s Disease Prediction Task

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

    Författare :Maryam Kheirkhahzadeh; [2023]
    Nyckelord :Speech classification; Alzheimer’s disease detection; GPT-3; BERT; Text embedding; Dementia; wav2vec2.0; Klassificering av tal; detektion av Alzheimer’s sjukdom; GPT-3; BERT; textinbäddning; demens; wav2vec2.0;

    Sammanfattning : Alzheimer’s sjukdom är en neurodegenerativ sjukdom som leder till demens. Den kan börja tyst i de tidiga stadierna och fortsätta under åren till en allvarlig och obotlig fas. Språkstörningar uppstår ofta som ett av de tidiga symptomen och kan till slut leda till fullständig mutism i de avancerade stadierna av sjukdomen. LÄS MER

  3. 12. Towards End-User Understanding: Exploring Explanations For Profanity Detection

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Noah Öberg; [2023]
    Nyckelord :;

    Sammanfattning : Current text classification models can accurately identify instances of specific categories, such as hate speech or bad language, but they often don’t provide clear explanations to the end user for their decisions. This can lead to confusion or mistrust in the results, especially in sensitive applications where the consequences of misclassification can be significant. LÄS MER

  4. 13. Evaluating machine learning models for text classification

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Jonas Lilja; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : This thesis will explore the use of AWS machine learning services that enable natural language processing (NLP). More specifically, this work will focus on sentiment analysis of product and service reviews written in Swedish. LÄS MER

  5. 14. The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM

    Master-uppsats, KTH/Matematik (Inst.)

    Författare :Oscar Blommegård; [2023]
    Nyckelord :The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM; Hämtningsförstärkta språkmodeller; Natural Language Processing; Transformers; Djupinlärning; Textklassificering;

    Sammanfattning : Large Language Models (LLMs) have demonstrated impressive results across various language technology tasks. By training on large corpora of diverse text collections from the internet, these models learn to process text effectively, allowing them to acquire comprehensive world knowledge. LÄS MER

  7. 15. IMPROVING NONDISCRIMINATIVE CLASSIFIERS WITH THE HELP OF CLUSTERING : Enhancing Text Classification: Using Clustering For Improved Classifier Performance

    Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Martin Mickels; [2023]
    Nyckelord :classification; waste; Avfallsloggen; clustering; nondiscriminative;

    Sammanfattning : A common classification task of today is classifying resources that consist of words. Nondiscriminative classifiers are a popular type of classifiers for such classification. This paper presents a study that determines whether a method of using clusters of words found in training data can be utilized for improved classifier performance. LÄS MER