Sökning: "testing machine"

Visar resultat 1 - 5 av 722 uppsatser innehållade orden testing machine.

  1. 1. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Zeyuan Wu; [2024]
    Nyckelord :Machine Learning; Diagnosis of Sepsis; XGBoost; Logistic Regression; Mathematics and Statistics;

    Sammanfattning : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. LÄS MER

  2. 2. Power Profiling: Understanding the Impact of CPU Workloads on Container and Virtual Machine Power Efficiency

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Johan Huusko; [2024]
    Nyckelord :;

    Sammanfattning : Data centers power consumption represent a substantial amount of the global power consumption. While hardware has improved over the years, this study focuses on the software side of optimization, looking at the power consumption differences in containers and virtual machines. LÄS MER

  3. 3. 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

  4. 4. Predicting inflow and infiltration to wastewater networks based on temperature measurements

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Martin Åsell; [2024]
    Nyckelord :Inflow and Infiltration; I I; CNN; Linear regression;

    Sammanfattning : Sewer pipelines are deteriorating due to aging and sub optimal material selections, leading to the infiltration of clean ground and rainfall water into the pipes. It is estimated that a significant portion (up to 40-50%) of the water entering wastewater treatment plants is actually clean infiltrated water. LÄS MER

  5. 5. An Empirical Survey of Bandits in an Industrial Recommender System Setting

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

    Författare :Tobias Schwarz; Johan Brandby; [2023-09-21]
    Nyckelord :computer science; industrial application; machine learning; reinforcement learning; multi-armed bandits; MAB; contextual multi-armed bandits; survey; batch learning;

    Sammanfattning : In this thesis, the effects of incorporating unstructured data—images in the wild—in contextual multi-armed bandits are investigated, when used within a recommender system setting, which focuses on picture-based content suggestion. The idea is to employ image features, extracted by a pre-trained convolutional neural network, and study the resulting bandit behaviors when including respective excluding this information in the typical context creation, which normally relies on structured data sources—such as metadata. LÄS MER