Essays about: "Missing data handling"
Showing result 1 - 5 of 29 essays containing the words Missing data handling.
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1. Designing a reactive feedback feature for end-users in web-based media software
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Customer feedback is essential for improving a company's products or services and increasing customer satisfaction. Despite its value, user involvement faces many challenges, such as low user motivation and feedback with missing context information. READ MORE
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2. MODELING INPUT VARIABLE AGE IN SEPSIS PREDICTION USING TREE-BASED MODELS
University essay from Uppsala universitet/Statistiska institutionenAbstract : 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
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3. An Empirical Investigation of The Effect of Proxy Response and The Merits of Its Remedial Measures
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : In the event of missing data, substitution of data from proxy sources are usually considered a very useful alternative when available to avoid the problem of missingness. Nonetheless, research has also shown that this approach often induces “response bias”. READ MORE
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4. Data Classification System Based on Combination Optimized Decision Tree : A Study on Missing Data Handling, Rough Set Reduction, and FAVC Set Integration
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Data classification is a novel data analysis technique that involves extracting valuable information with potential utility from databases. It has found extensive applications in various domains, including finance, insurance, government, education, transportation, and defense. READ MORE
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5. Improving Missing Data Imputation using Generative Adversarial Network-based Methods
University essay from Lunds universitet/Matematisk statistikAbstract : 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