Results 31 to 40 of about 283,145 (183)
Biomedical Engineering Advances, 2022 The effect of horror sound on electro-cardiac activity is not yet sufficiently explored despite recommendable research on different genres of music and sound. Detecting the impact of these stimuli is a complex task.
Bikash K. Pradhan +6 more
doaj +1 more source
Class imbalance ensemble learning based on the margin theory [PDF]
, 2018 The proportion of instances belonging to each class in a data-set plays an important role in machine learning. However, the real world data often suffer from class imbalance.
Feng, Wei +2 more
core +2 more sources
Towards A Deeper Geometric, Analytic and Algorithmic Understanding of Margins
, 2015 Given a matrix $A$, a linear feasibility problem (of which linear classification is a special case) aims to find a solution to a primal problem $w: A^Tw > \textbf{0}$ or a certificate for the dual problem which is a probability distribution $p: Ap ...
Peña, Javier, Ramdas, Aaditya
core +1 more source
Using Machine Learning and Candlestick Patterns to Predict the Outcomes of American Football Games
Applied Sciences, 2020 Match outcome prediction is a challenging problem that has led to the recent rise in machine learning being adopted and receiving significant interest from researchers in data science and sports. This study explores predictability in match outcomes using
Yu-Chia Hsu
doaj +1 more source
On Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics
, 2018 Margin enlargement over training data has been an important strategy since perceptrons in machine learning for the purpose of boosting the robustness of classifiers toward a good generalization ability.
Huang, Yifei, Yao, Yuan, Zhu, Weizhi
core +1 more source
Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy [PDF]
Scientific Reports, 2020 AbstractGliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clustering method is proposed to discriminate glioma margin.
Leclerc, Pierre +9 more
openaire +3 more sources
Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema
BMC Ophthalmology, 2019 Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals.
Jin Mo Ahn +4 more
doaj +1 more source
Statistical Mechanics of Soft Margin Classifiers
, 2001 We study the typical learning properties of the recently introduced Soft Margin Classifiers (SMCs), learning realizable and unrealizable tasks, with the tools of Statistical Mechanics.
A. Buhot +30 more
core +1 more source
Alternative Strategies in Learning Nonlinear Soft Margin Support Vector Machines
Informatica Economica, 2014 The aims of the paper are multifold, to propose a new method to determine a suitable value of the bias corresponding to the soft margin SVM classifier and to experimentally evaluate the quality of the found value against one of the standard expression of the bias computed in terms of the support vectors.
Catalina COCIANU +2 more
openaire +2 more sources
Cancers, 2022 The intraoperative assessment of tumor margins of head and neck cancer is crucial for complete tumor resection and patient outcome. The current standard is to take tumor biopsies during surgery for frozen section analysis by a pathologist after H&E staining.
David Pertzborn +7 more
openaire +2 more sources