Abstract: Many machine learning applications deal with high-dimensional data. To make computations feasible and learning more efficient, it is often desirable to reduce the dimensionality of the input ...
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How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
To compare dimensionality-reduction methods for building prognostic models predicting metastasis-free survival (MFS) in localized prostate adenocarcinoma (PCa) patients treated with ...
This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
What is a 4D Rubik's Cube? A 4D Rubik's Cube, often called a hypercube puzzle, 3x3x3x3, or 3^4, is a conceptual extension of the classic Rubik's Cube into a fourth spatial dimension. Its fundamental ...
ABSTRACT: This study investigates the effect of vertical scaling on fractal dimension (FD) estimation for failure surfaces in opencast mines to improve surface roughness characterization for slope ...
The advancement of tactile sensing in robotics and prosthetics is constrained by the trade-off between spatial and temporal resolution in artificial tactile sensors. To address this limitation, we ...
ABSTRACT: Polychlorinated biphenyls are toxic, man-made, organic chemicals that have hazardous effects on the environment and our health, yet their occurrence in sediments and water from drinking ...
Abstract: Time series analysis is a critical task across various scientific and industrial domains, enabling the extraction of valuable insights from temporal data. High dimensionality of time series ...
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