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Showing result 1 - 5 of 38 essays matching the above criteria.

  1. 1. MODELING INPUT VARIABLE AGE IN SEPSIS PREDICTION USING TREE-BASED MODELS

    University essay from Uppsala universitet/Statistiska institutionen

    Author : Oscar Wastesson; [2023]
    Keywords : Machine learning; decision trees; sepsis; classification;

    Abstract : Last observation carried forward (LOCF) is a common imputation method, regularly used for clinical data. It is based on the principle that the most recent observation that is known is carried forward to replace missing values. READ MORE

  3. 2. Implementing SAE Techniques to Predict Global Spectacles Needs

    University essay from Högskolan Dalarna/Institutionen för information och teknik

    Author : Yuxue Zhang; [2023]
    Keywords : small area estimation; area-level model; empirical best linear unbiased prediction EBLUP ; generalized linear mixed models; Conditional Autoregressive; spatial correlation; spectacle needs; assistive products; auxiliary data; hglm; relative standard error; simulation;

    Abstract : This study delves into the application of Small Area Estimation (SAE) techniques to enhance the accuracy of predicting global needs for assistive spectacles. By leveraging the power of SAE, the research undertakes a comprehensive exploration, employing arange of predictive models including Linear Regression (LR), Empirical Best Linear Unbiased Prediction (EBLUP), hglm (from R package) with Conditional Autoregressive (CAR), and Generalized Linear Mixed Models (GLMM). READ MORE

  4. 3. Silicon Drift Detector Simulations for Energy-Dispersive X-ray Spectroscopy in Scanning Electron Microscopy

    University essay from Stockholms universitet/Fysikum

    Author : Sebbe Blokhuizen; [2023]
    Keywords : X-ray spectroscopy; Silicon drift detector; Scanning Electron Microscopy; Detector Simulation;

    Abstract : Scanning Electron Microscopy combined with Energy Dispersive X-ray Spectroscopy (SEM-EDS) is a widely applied elemental microanalysis method. The integration of silicon drift detectors (SDDs) has notably enhanced EDS performance, enabling precise elemental identification due to its large sensitive area and low output capacitance. READ MORE

  5. 4. Data-Driven Success in Infrastructure Megaprojects. : Leveraging Machine Learning and Expert Insights for Enhanced Prediction and Efficiency

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

    Author : David E.G. Nordmark; [2023]
    Keywords : Megaproject; Small sample size; Project management; Random forest; Critical success factors; Feature selection; Recursive feature elimination; Megaprojekt; Små dataurval; Projektledning; Random forest; Kritiska framgångsfaktorer; Variabel urval; Rekursiv variabel eliminering;

    Abstract : This Master's thesis utilizes random forest and leave-one-out cross-validation to predict the success of megaprojects involving infrastructure. The goal was to enhance the efficiency of the design and engineering phase of the infrastructure and construction industries. READ MORE

  6. 5. Improving Missing Data Imputation using Generative Adversarial Network-based Methods

    University essay from Lunds universitet/Matematisk statistik

    Author : Hanna Anderberg; Sofia Wadell; [2023]
    Keywords : Missing Values; Data Imputation; Generative Adversarial Network; GAIN; CTGAN; Mathematics and Statistics;

    Abstract : In a modern context, organizations increasingly rely on data analysis and the importance of data quality have accordingly become even more crucial. In this context, missing values pose a significant challenge compromising the utility of the data. READ MORE