Results 11 to 20 of about 1,003,291 (283)

Faster Support Vector Machines [PDF]

ACM Journal of Experimental Algorithmics, 2019
The time complexity of support vector machines (SVMs) prohibits training on huge datasets with millions of data points. Recently, multilevel approaches to train SVMs have been developed to allow for time-efficient training on huge datasets.
Sebastian Schlag, Matthias Schmitt, Christian Schulz   +2 more
openaire   +6 more sources

Selection of Specialization Class Using Support Vector Machine (SVM) Method in Sekolah Menengah Atas Negeri 1 Ambon

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021
The curriculum is a plan to form the abilities and character of children based on a standard. One of its form is the division of specialization classes at the high school level.
Stevanny Tamaela, Yopi Andry Lesnussa, Venn Yan Ishak Ilwaru   +2 more
doaj   +1 more source

Improvement of Time Forecasting Models Using Machine Learning for Future Pandemic Applications Based on COVID-19 Data 2020–2022

Diagnostics, 2023
Improving forecasts, particularly the accuracy, efficiency, and precision of time-series forecasts, is becoming critical for authorities to predict, monitor, and prevent the spread of the Coronavirus disease.
Abdul Aziz K Abdul Hamid, Wan Imanul Aisyah Wan Mohamad Nawi, Muhamad Safiih Lola, Wan Azani Mustafa, Siti Madhihah Abdul Malik, Syerrina Zakaria, Elayaraja Aruchunan, Nurul Hila Zainuddin, R.U. Gobithaasan, Mohd Tajuddin Abdullah   +9 more
doaj   +1 more source

Overcome Support Vector Machine Diagnosis Overfitting

Cancer Informatics, 2014
Support vector machines (SVMs) are widely employed in molecular diagnosis of disease for their efficiency and robustness. However, there is no previous research to analyze their overfitting in high-dimensional omics data based disease diagnosis, which is
Henry Han, Xiaoqian Jiang
doaj   +2 more sources

Two-Phase Indefinite Kernel Support Vector Machine

Jisuanji kexue yu tansuo, 2020
Recently, indefinite kernel support vector machine (IKSVM) has attracted great attention in the machine learning community as more and more indefinite metric kernel matrices have occurred.
SHI Na, XUE Hui, WANG Yunyun
doaj   +1 more source

Support vector machine for functional data classification [PDF]

, 2005
In many applications, input data are sampled functions taking their values in infinite dimensional spaces rather than standard vectors. This fact has complex consequences on data analysis algorithms that motivate modifications of them.
Aronszajn, Besse, Biau, Cardot, Cardot, Cristianini, Dauxois, Deville, Evgeniou, Fabrice Rossi, Ferré, Francois, Frank, Hastie, Hastie, Hastie, Hastie, Hoerl, James, Leurgans, Lin, Mallat, Marx, Nathalie Villa, Pezzulli, Ramsay, Ramsay, Rossi, Rossi, Rossi, Rossi, Sandberg, Sandberg, Smola, Smola, Steinwart, Steinwart, Stinchcombe, Vapnik, Vert, Villa   +40 more
core   +7 more sources

MRI brain classification using support vector machine [PDF]

, 2011
The field of medical imaging gains its importance with increase in the need of automated and efficient diagnosis in a short period of time. Other than that, medical image retrieval system is to provide a tool for radiologists to retrieve the images ...
Abdullah, N. B., Kamal, N. F. B., Othman, Mohd. Fauzi   +2 more
core   +1 more source

Solving Support Vector Machine with Many Examples

Journal of Telecommunications and Information Technology, 2023
Various methods of dealing with linear support vector machine (SVM) problems with a large number of examples are presented and compared. The author believes that some interesting conclusions from this critical analysis applies to many new optimization ...
Paweł Białoń
doaj   +1 more source

Model Selection for Support Vector Machine Classification [PDF]

, 2002
We address the problem of model selection for Support Vector Machine (SVM) classification. For fixed functional form of the kernel, model selection amounts to tuning kernel parameters and the slack penalty coefficient $C$.
Burges, Carl Gold, Chapelle, Cristianini, Jaakkola, Krauth, Kwok, Kwok, MacKay, MacKay, Neal, Opper, Opper, Peter Sollich, Press, Smola, Sollich, Vapnik, Vapnik, Vapnik, Wahba, Williams, Williams   +22 more
core   +4 more sources

Quantum-Enhanced Support Vector Machine for Sentiment Classification

IEEE Access, 2023
Quantum computers have potential computational abilities such as speeding up complex computations, parallelism by superpositions, and handling large data sets. Moreover, the field of natural language processing (NLP) is rapidly attracting researchers and
Fariska Zakhralativa Ruskanda, Muhammad Rifat Abiwardani, Rahmat Mulyawan, Infall Syafalni, Harashta Tatimma Larasati   +4 more
doaj   +1 more source