Essays about: "dataset quality"

Showing result 1 - 5 of 331 essays containing the words dataset quality.

1. 1. Reconstructing point patterns from spatially aggregated data

   University essay from Göteborgs universitet/Institutionen för matematiska vetenskaper

   Author : Jens Michelsen; [2024-03-13]
   Keywords : lorem; ipsum; dolor; sit; amet; consectetur; adipisicing; elit; sed; do.;

   Abstract : In this thesis we explore the ability to reconstruct samples (point configurations) from a point process, based only on the information contained in spatially aggregated data, namely the number of points in the partitions of a larger region. The ability to reconstruct a point configuration, in such a way that it retains most of it’s statistical properties, could be useful in cases where one is faced with a mixed dataset; some regions containing the full point configuration data, while other regions only contain aggregated data, i. READ MORE

3. 2. Variational AutoEncoders and Differential Privacy : balancing data synthesis and privacy constraints

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

   Author : Baptiste Bremond; [2024]
   Keywords : TVAE; Differential privacy; Tabular data; Synthetic data; DP-SGD; TVAE; differentiell integritet; tabelldata; syntetiska data; DP-SGD;

   Abstract : This thesis investigates the effectiveness of Tabular Variational Auto Encoders (TVAEs) in generating high-quality synthetic tabular data and assesses their compliance with differential privacy principles. The study shows that while TVAEs are better than VAEs at generating synthetic data that faithfully reproduces the distribution of real data as measured by the Synthetic Data Vault (SDV) metrics, the latter does not guarantee that the synthetic data is up to the task in practical industrial applications. READ MORE

4. 3. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting

   University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesign

   Author : Elie Roudiere; [2024]
   Keywords : Railway; Track geometry; Machine learning; Statistics; Predictive maintenance; Botniabanan; Järnväg; spårgeometri; maskininlärning; statistik; förebyggande underhåll; Botniabanan;

   Abstract : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. READ MORE

5. 4. 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

6. 5. Implementing End-to-End MLOps for Enhanced Steel Production

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

   Author : Marcus Westin; Jacob Berggren; [2024]
   Keywords : MLOps; Azure ML; Machine Learning; Computer Science; Microsoft Azure; MLOps; Azure ML; Maskininlärning; Datavetenskap; Microsoft Azure;

   Abstract : Steel production companies must utilize new technologies and innovations to stay ahead of a highly competitive market. Recently, there has been a focus on Industry 4.0, which involves the digitalization of production to integrate with newer technologies such as cloud solutions and the Internet of Things (IoT). READ MORE