Sökning: "Topic interpretability"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden Topic interpretability.

  1. 1. Applying the Shadow Rating Approach: A Practical Review

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Viktor Barry; Carl Stenfelt; [2023]
    Nyckelord :Shadow Rating; probability of default; low default portfolio; credit risk; statistical learning; financial regulation; Basel; Pluto and Tasche; Skuggrating; sannolikhet av fallissemang; lågfallissemangsportfölj; kreditrisk; statistisk inlärning; finansiella regelverk; Basel; Pluto och Tasche;

    Sammanfattning : The combination of regulatory pressure and rare but impactful defaults together comprise the domain of low default portfolios, which is a central and complex topic that lacks clear industry standards. A novel approach that utilizes external data to create a Shadow Rating model has been proposed by Ulrich Erlenmaier. LÄS MER

  3. 2. Anchor-based Topic Modeling with Human Interpretable Results

    Master-uppsats, Linköpings universitet/Interaktiva och kognitiva system

    Författare :Henrik Andersson; [2020]
    Nyckelord :topic models; anchor-based; anchor words; efficient; human interpretable;

    Sammanfattning : Topic models are useful tools for exploring large data sets of textual content by exposing a generative process from which the text was produced. Anchor-based topic models utilize the anchor word assumption to define a set of algorithms with provable guarantees which recover the underlying topics with a run time practically independent of corpus size. LÄS MER

  4. 3. Characterisation of a developer’s experience fields using topic modelling

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Vincent Déhaye; [2020]
    Nyckelord :topic modelling natural language processing git developer latent dirichlet allocation non-negative matrix factorization topic coherence;

    Sammanfattning : Finding the most relevant candidate for a position represents an ubiquitous challenge for organisations. It can also be arduous for a candidate to explain on a concise resume what they have experience with. LÄS MER

  5. 4. Leveraging Explainable Machine Learning to Raise Awareness among Preadolescents about Gender Bias in Supervised Learning

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

    Författare :Gaspar Isaac Melsion Perez; [2020]
    Nyckelord :explainable AI; interpretability; education; children; gender; bias; machine learning; human-computer interaction; förklarbar AI; tolkbarhet; utbildning; barn; kön; bias; maskininlärning; människa-datorinteraktion;

    Sammanfattning : Machine learning systems have become ubiquitous into our society. This has raised concerns about the potential discrimination that these systems might exert due to unconscious bias present in the data, for example regarding gender and race. LÄS MER

  7. 5. Evolving Text Classifier Using Genetic Programming

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Hoang Ngo; Ema Eminagic; [2020]
    Nyckelord :genetic programming; evolutionary algorithm; evolutionary computation; text classification; n-grams; natural language processing; Technology and Engineering;

    Sammanfattning : Text classification is one of the main tasks within the field of natural language processing, which has been growing significantly during the last decade with applications in different industries. Despite different approaches to text classification showing good results, such as Machine Learning and Deep Learning, their shortcomings give substance to the need for further research on other approaches. LÄS MER