Essays about: "Multiple Regression models thesis"
Showing result 1 - 5 of 114 essays containing the words Multiple Regression models thesis.
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1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE
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2. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
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3. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
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4. Predicting Counter-Strike Matches using Machine Learning Models
University essay from Lunds universitet/Statistiska institutionenAbstract : Sports betting is a widespread industry where predictive modeling play a big role. The goal of this thesis is to explore the possibilities of machine learning within the realm of e-sport prediction. The data used for this thesis is publicly available data was recorded over a three year period. READ MORE
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5. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE
