This is the Windows app named BudgetedSVM whose latest release can be downloaded as BudgetedSVM_v1.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named BudgetedSVM with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
BudgetedSVM
Ad
DESCRIPTION
We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of high-dimensional examples within minutes on a regular personal computer. We provide command-line and Matlab interfaces to BudgetedSVM, efficient API for handling large-scale, high-dimensional data sets, as well as detailed documentation to help developers use and further extend the toolbox.
Features
- We provide efficient implementations of algorithms for highly-scalable non-linear SVM training.
- The toolbox can handle large, high-dimensional data sets that cannot be loaded into memory.
- The toolbox requires constant memory to train models that solve highly non-linear problems.
- We provide command-line and Matlab interfaces to BudgetedSVM.
- We provide an efficient API that provides functionalities for handling large, high-dimensional data sets. Using BudgetedSVM API, data sets with millions data points and/or features are easily handled.
- For more details, please see the documentation included in the download package.
- Published under industry-friendly Modified BSD licence.
Audience
Information Technology, Science/Research, End Users/Desktop
Programming Language
C++
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/budgetedsvm/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
