Essays about: "high-dimensional data"
Showing result 1 - 5 of 123 essays containing the words high-dimensional data.
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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
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2. Geometry of high dimensional Gaussian data
University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakultetenAbstract : Collected data may simultaneously be of low sample size and high dimension. Such data exhibit some geometric regularities consisting of a single observation being a rotation on a sphere, and a pair of observations being orthogonal. This thesis investigates these geometric properties in some detail. READ MORE
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3. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
University essay from Lunds universitet/Statistiska institutionenAbstract : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. READ MORE
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4. On Expressing Automotive Maneuvers with SFC
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Conventional methods for testing autonomous driving software often involve dealing with a large number of dimensions, which can complicate the processing and analysis of test datasets. Therefore, there is a pressing need to develop a more efficient approach that is both time and cost-effective. READ MORE
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5. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. READ MORE