Essays about: "ALGORITHM"
Showing result 1 - 5 of 5617 essays containing the word ALGORITHM.
-
1. Feature Selection for Microarray Data via Stochastic Approximation
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. READ MORE
-
2. A space-time shape for easier spatiotemporal visualization in traffic networks
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Modern big data systems are enabling new possibilities that never were thought possible in the past. The ability to gather massive data on an individual level has made fields like space-time geography bloom in the latest decennia. The usage of shapes in a 3D space allows us to visualize certain phenomena over time. READ MORE
-
3. Robust Object Recognition and Tracking with Drones
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The Skara Skyddsängel project explores an innovative method of providing illumination for cyclists along a 20km unlit bike lane using drones. Current GNSS approach performs generally well but further improvements are need for better robustness. Consequently, this thesis project is raised to seek a robust solution in the field of computer vision. READ MORE
-
4. A Verified QBF Solver
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Quantified Boolean Formulas (QBFs) extend propositional logic with universal and existential quantification over Boolean variables. A QBF is satisfiable if and only if there is an assignment of Boolean values to the free variables that makes the formula true, and a QBF solver is a software tool determining if a given QBF is satisfiable. READ MORE
-
5. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques
University essay from Lunds universitet/Matematisk statistikAbstract : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. READ MORE
