Sökning: "assessment of learning"

Visar resultat 6 - 10 av 775 uppsatser innehållade orden assessment of learning.

  1. 6. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

    Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Alexander Florean; [2024]
    Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

    Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

  3. 7. Risky Business: Quantitative Risk Assessments as Enabling Devices in Cybersecurity

    Magister-uppsats, Lunds universitet/Avdelningen för Riskhantering och Samhällssäkerhet

    Författare :Colette Alexander; [2024]
    Nyckelord :Quantitative risk assessment; cybersecurity; enabling device; Technology and Engineering;

    Sammanfattning : Quantitative risk assessment (QRA) is a growing practice in the cybersecurity field. This paper examines QRA the use in various industries and the problems with its use. The focus of the qualitative research is to understand why cybersecurity organizations might want to use QRA even if it produces untrue and potentially problematic results. LÄS MER

  4. 8. Dynamik och tillförlighet i finansiell prognostisering : En analys av djupinlärningsmodeller och deras reaktion på marknadsmanipulation

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Aya Zawahri; Nanci Ibrahim; [2024]
    Nyckelord :LOB; market manipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.; LOB; marknadsmanipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.;

    Sammanfattning : Under åren har intensiv forskning pågått för att förbättra maskininlärningsmodellers förmåga att förutse marknadsrörelser. Trots detta har det, under finanshistorien, inträffat flera händelser, såsom "Flash-crash", som har påverkat marknaden och haft dramatiska konsekvenser för prisrörelserna. LÄS MER

  5. 9. Exploring serial positioning effects in Claeson-Dahl's Test for verbal learning and retention – a naturalistic study

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

    Författare :Hampus Fritz; [2024]
    Nyckelord :serial positioning effect; Claeson-Dahl’s Test for verbal learning and retention; neuropsychology; memory; word list; Seriepositionseffekten; Claeson-Dahls Test för inlärning och minne; neuropsykolog; minne; ordlista; Social Sciences;

    Sammanfattning : Serial positioning effects and the derived recency ratio has shown increasing promise as clinical tools for evaluating neurocognitive disorders. These measures have remained unexplored in Claeson-Dahl’s Test for verbal learning and retention (CDT). LÄS MER

  7. 10. Virtual H&E Staining Using PLS Microscopy and Neural Networks

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Sally Vizins; Hanna Råhnängen; [2024]
    Nyckelord :Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

    Sammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER