Results 41 to 50 of about 285,439 (304)

Large-Margin Regularized Softmax Cross-Entropy Loss

IEEE Access, 2019
Softmax cross-entropy loss with L2 regularization is commonly adopted in the machine learning and neural network community. Considering that the traditional softmax cross-entropy loss simply focuses on fitting or classifying the training data accurately ...
Xiaoxu Li, Dongliang Chang, Tao Tian, Jie Cao   +3 more
doaj   +1 more source

Performance Analysis of different Machine Learning Models for Intrusion Detection Systems

Journal of Engineering, 2022
In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks.
salim Qadir Mohammed, Mohammed A. Hussein   +1 more
doaj   +1 more source

Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository

, 2018
Machine learning qualifies computers to assimilate with data, without being solely programmed [1, 2]. Machine learning can be classified as supervised and unsupervised learning.
Arif, Rezoana Bente, Khan, Mohammad Mahmudur Rahman, Oishe, Mahjabin Rahman, Siddique, Md. Abu Bakr   +3 more
core   +1 more source

Investigating the effect of sound in horror clip on the cardiac electrophysiology of young adults using wavelet packet decomposition and machine learning classifiers

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, Chinmaya R. Mishra, Maciej Jarzębski, J Sivaraman, Sirsendu S. Ray, Satyapriya Mohanty, Kunal Pal   +6 more
doaj   +1 more source

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

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, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho, Ungsoo S. Kim   +4 more
doaj   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +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

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source