Sökning: "Rafael M. Martins"

Hittade 2 avhandlingar innehållade orden Rafael M. Martins.

  1. 1. Visual Analytics for Explainable and Trustworthy Machine Learning

    Författare :Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

    Sammanfattning : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. LÄS MER

  3. 2. Visualizing Cluster Patterns at Scale : A Model and a Library

    Författare :Elio Ventocilla; Maria Riveiro; Göran Falkman; Rafael M. Martins; Katerina Vrostou; Högskolan i Skövde; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Visual analytics; cluster patterns; big data; unsupervised learning; multidimensional projections; vector quantization; progressive visual analytics; Skövde Artificial Intelligence Lab SAIL ; Skövde Artificial Intelligence Lab SAIL ;

    Sammanfattning : Large quantities of data are being collected and analyzed by companies and institutions, with the aim of extracting knowledge and value. When little is known about the data at hand, analysts engage in exploratory data analysis to achieve a better understanding. LÄS MER