Essays about: "Utvärdering av Modellprestanda"

Found 2 essays containing the words Utvärdering av Modellprestanda.

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

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Alexander Florean; [2024]
    Keywords : 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;

    Abstract : 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. READ MORE

  3. 2. Sign of the Times : Unmasking Deep Learning for Time Series Anomaly Detection

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Daniel Richards Ravi Arputharaj; [2023]
    Keywords : Anomaly detection; multivariate time series data; deep learning models; model complexity; resource-constrained systems; Variational Autoencoders VAEs ; Convolutional Variational Autoencoders; evaluation metrics in time series; Anomalidetektering; Multivariata tidsseriedata; Djupinlärningsmodeller; Modellkomplexitet; Resursbegränsade system; Variational Autoencoders VAEs ; Konvolutionella Variational Autoencoders; Utvärderingsmått inom tidsserier;

    Abstract : Time series anomaly detection has been a longstanding area of research with applications across various domains. In recent years, there has been a surge of interest in applying deep learning models to this problem domain. READ MORE